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Publications of David B. Dunson    :chronological  alphabetical  combined  bibtex listing:

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Books

  1. Gelman, A; Carlin, JB; Stern, HS; Dunson, DB; Vehtari, A; Rubin, DB, Bayesian data analysis, third edition (January, 2013), pp. 1-646, ISBN 9781439840955  [abs]

Papers Published

  1. Lin, L; Saparbayeva, B; Zhang, MM; Dunson, DB, Accelerated algorithms for convex and non-convex optimization on manifolds, Machine Learning, vol. 114 no. 3 (March, 2025) [doi]  [abs]
  2. Dombowsky, A; Dunson, DB, Bayesian Clustering via Fusing of Localized Densities, Journal of the American Statistical Association (January, 2025) [doi]  [abs]
  3. Winter, S; Mahzarnia, A; Anderson, RJ; Han, ZY; Tremblay, J; Stout, JA; Moon, HS; Marcellino, D; Dunson, DB; Badea, A, Brain network fingerprints of Alzheimer's disease risk factors in mouse models with humanized APOE alleles., Magn Reson Imaging, vol. 114 (December, 2024), pp. 110251 [doi]  [abs]
  4. Zhu, Y; Peruzzi, M; Li, C; Dunson, DB, Radial neighbours for provably accurate scalable approximations of Gaussian processes, Biometrika, vol. 111 no. 4 (December, 2024), pp. 1151-1167 [doi]  [abs]
  5. Sarkar, A; Cominetti, O; Montoliu, I; Hosking, J; Pinkney, J; Martin, F-P; Dunson, DB, Bayesian semiparametric inference in longitudinal metabolomics data., Scientific reports, vol. 14 no. 1 (December, 2024), pp. 31336 [doi]  [abs]
  6. Huang, J; Morsomme, R; Dunson, D; Xu, J, Detecting changes in the transmission rate of a stochastic epidemic model., Statistics in medicine, vol. 43 no. 10 (May, 2024), pp. 1867-1882 [doi]  [abs]
  7. Chakraborty, A; Ou, R; Dunson, DB, Bayesian inference on high-dimensional multivariate binary responses., Journal of the American Statistical Association, vol. 119 no. 548 (January, 2024), pp. 2560-2571 [doi]  [abs]
  8. Melikechi, O; Dunson, DB, Ellipsoid fitting with the Cayley transform., IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol. 72 (January, 2024), pp. 70-83 [doi]  [abs]
  9. Datta, J; Banerjee, S; Dunson, DB, Nonparametric Bayes multiresolution testing for high-dimensional rare events, Journal of Nonparametric Statistics (January, 2024) [doi]  [abs]
  10. Winter, S; Campbell, T; Lin, L; Srivastava, S; Dunson, DB, Emerging Directions in Bayesian Computation, Statistical Science, vol. 39 no. 1 (January, 2024), pp. 62-89 [doi]  [abs]
  11. Zhai, Q; Ye, Z; Li, C; Revie, M; Dunson, DB, Modeling Recurrent Failures on Large Directed Networks, Journal of the American Statistical Association (January, 2024) [doi]  [abs]
  12. Jin, B; Herring, AH; Dunson, D, SPATIAL PREDICTIONS ON PHYSICALLY CONSTRAINED DOMAINS: APPLICATIONS TO ARCTIC SEA SALINITY DATA, Annals of Applied Statistics, vol. 18 no. 2 (January, 2024), pp. 1596-1617 [doi]  [abs]
  13. Papamarkou, T; Skoularidou, M; Palla, K; Aitchison, L; Arbel, J; Dunson, D; Filippone, M; Fortuin, V; Hennig, P; Hernández-Lobato, JM; Hubin, A; Immer, A; Karaletsos, T; Khan, ME; Kristiadi, A; Li, Y; Mandt, S; Nemeth, C; Osborne, MA; Rudner, TGJ; Rügamer, D; Teh, YW; Welling, M; Wilson, AG; Zhang, R, Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI, Proceedings of Machine Learning Research, vol. 235 (January, 2024), pp. 39556-39586  [abs]
  14. Tang, T; Mak, S; Dunson, D, Hierarchical Shrinkage Gaussian Processes: Applications to Computer Code Emulation and Dynamical System Recovery, SIAM-ASA Journal on Uncertainty Quantification, vol. 12 no. 4 (January, 2024), pp. 1085-1112 [doi]  [abs]
  15. Chandra, NK; Dunson, DB; Xu, J, Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis, Journal of the American Statistical Association (January, 2024) [doi]  [abs]
  16. Buch, DA; Johndrow, JE; Dunson, DB, Explaining transmission rate variations and forecasting epidemic spread in multiple regions with a semiparametric mixed effects SIR model., Biometrics, vol. 79 no. 4 (December, 2023), pp. 2987-2997 [doi]  [abs]
  17. Xu, J; Li, Y; Yang, H; Dunson, D; Daubechies, I, PiPs: A kernel-based optimization scheme for analyzing non-stationary 1D signals, Applied and Computational Harmonic Analysis, vol. 66 (September, 2023), pp. 1-17 [doi]  [abs]
  18. Rigon, T; Herring, AH; Dunson, DB, A generalized Bayes framework for probabilistic clustering., Biometrika, vol. 110 no. 3 (September, 2023), pp. 559-578 [doi]  [abs]
  19. Liu, R; Li, M; Dunson, DB, PPA: Principal parcellation analysis for brain connectomes and multiple traits., NeuroImage, vol. 276 (August, 2023), pp. 120214 [doi]  [abs]
  20. Talbot, A; Dunson, D; Dzirasa, K; Carlson, D, Estimating a brain network predictive of stress and genotype with supervised autoencoders., J R Stat Soc Ser C Appl Stat, vol. 72 no. 4 (August, 2023), pp. 912-936 [doi]  [abs]
  21. Jin, B; Dunson, DB; Rager, JE; Reif, DM; Engel, SM; Herring, AH, Bayesian matrix completion for hypothesis testing., Journal of the Royal Statistical Society. Series C, Applied statistics, vol. 72 no. 2 (May, 2023), pp. 254-270 [doi]  [abs]
  22. Mahzarnia, A; Stout, JA; Anderson, RJ; Moon, HS; Yar Han, Z; Beck, K; Browndyke, JN; Dunson, DB; Johnson, KG; O'Brien, RJ; Badea, A, Identifying vulnerable brain networks associated with Alzheimer's disease risk., Cereb Cortex, vol. 33 no. 9 (April, 2023), pp. 5307-5322 [doi]  [abs]
  23. Gu, Y; Dunson, DB, Bayesian Pyramids: identifiable multilayer discrete latent structure models for discrete data, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 85 no. 2 (April, 2023), pp. 399-426 [doi]  [abs]
  24. Zito, A; Rigon, T; Dunson, DB, Inferring taxonomic placement from DNA barcoding aiding in discovery of new taxa, Methods in Ecology and Evolution, vol. 14 no. 2 (February, 2023), pp. 529-542 [doi]  [abs]
  25. Zhu, Y; Li, C; Dunson, DB, Classification Trees for Imbalanced Data: Surface-to-Volume Regularization, Journal of the American Statistical Association, vol. 118 no. 543 (January, 2023), pp. 1707-1717 [doi]  [abs]
  26. Zito, A; Rigon, T; Ovaskainen, O; Dunson, DB, Bayesian Modeling of Sequential Discoveries., Journal of the American Statistical Association, vol. 118 no. 544 (January, 2023), pp. 2521-2532 [doi]  [abs]
  27. Papadogeorgou, G; Bello, C; Ovaskainen, O; Dunson, DB, Covariate-Informed Latent Interaction Models: Addressing Geographic & Taxonomic Bias in Predicting Bird–Plant Interactions, Journal of the American Statistical Association, vol. 118 no. 544 (January, 2023), pp. 2250-2261 [doi]  [abs]
  28. Barrientos, AF; Sen, D; Page, GL; Dunson, DB, Bayesian Inferences on Uncertain Ranks and Orderings: Application to Ranking Players and Lineups, Bayesian Analysis, vol. 18 no. 3 (January, 2023), pp. 777-806 [doi]  [abs]
  29. Sachs, M; Sen, D; Lu, J; Dunson, D, Posterior Computation with the Gibbs Zig-Zag Sampler, Bayesian Analysis, vol. 18 no. 3 (January, 2023), pp. 909-927 [doi]  [abs]
  30. Li, D; Nguyen, P; Zhang, Z; Dunson, D, Tree representations of brain structural connectivity via persistent homology., Frontiers in neuroscience, vol. 17 (January, 2023), pp. 1200373 [doi]  [abs]
  31. Chandra, NK; Canale, A; Dunson, DB, Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering, Journal of Machine Learning Research, vol. 24 (January, 2023)  [abs]
  32. Chattopadhyay, S; Chakraborty, A; Dunson, DB, Nearest Neighbor Dirichlet Mixtures, Journal of Machine Learning Research, vol. 24 (January, 2023)  [abs]
  33. Gu, Y; Erosheva, EA; Xu, G; Dunson, DB, Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data, Journal of Machine Learning Research, vol. 24 (January, 2023)  [abs]
  34. Duan, LL; Dunson, DB, Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph, Journal of Machine Learning Research, vol. 24 (January, 2023)  [abs]
  35. Young, AL; van den Boom, W; Schroeder, RA; Krishnamoorthy, V; Raghunathan, K; Wu, H-T; Dunson, DB, Mutual information: Measuring nonlinear dependence in longitudinal epidemiological data., PLoS One, vol. 18 no. 4 (2023), pp. e0284904 [doi]  [abs]
  36. Legramanti, S; Rigon, T; Durante, D; Dunson, DB, EXTENDED STOCHASTIC BLOCK MODELS WITH APPLICATION TO CRIMINAL NETWORKS., The annals of applied statistics, vol. 16 no. 4 (December, 2022), pp. 2369-2395 [doi]  [abs]
  37. Chakraborty, A; Ovaskainen, O; Dunson, DB, BAYESIAN SEMIPARAMETRIC LONG MEMORY MODELS FOR DISCRETIZED EVENT DATA., The annals of applied statistics, vol. 16 no. 3 (September, 2022), pp. 1380-1399 [doi]  [abs]
  38. Melikechi, O; Young, AL; Tang, T; Bowman, T; Dunson, D; Johndrow, J, Limits of epidemic prediction using SIR models., Journal of mathematical biology, vol. 85 no. 4 (September, 2022), pp. 36 [doi]  [abs]
  39. Schiavon, L; Canale, A; Dunson, DB, Generalized infinite factorization models., Biometrika, vol. 109 no. 3 (September, 2022), pp. 817-835 [doi]  [abs]
  40. Dey, P; Zhang, Z; Dunson, DB, Outlier detection for multi-network data., Bioinformatics (Oxford, England), vol. 38 no. 16 (August, 2022), pp. 4011-4018 [doi]  [abs]
  41. Guha, S; Jung, R; Dunson, D, Predicting phenotypes from brain connection structure, Journal of the Royal Statistical Society. Series C: Applied Statistics, vol. 71 no. 3 (June, 2022), pp. 639-668 [doi]  [abs]
  42. Aliverti, E; Dunson, DB, COMPOSITE MIXTURE OF LOG-LINEAR MODELS WITH APPLICATION TO PSYCHIATRIC STUDIES., The annals of applied statistics, vol. 16 no. 2 (June, 2022), pp. 765-790 [doi]  [abs]
  43. Dunson, DB; Wu, HT; Wu, N, Graph based Gaussian processes on restricted domains, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 84 no. 2 (April, 2022), pp. 414-439 [doi]  [abs]
  44. Lum, K; Dunson, DB; Johndrow, J, Closer than they appear: A Bayesian perspective on individual-level heterogeneity in risk assessment, Journal of the Royal Statistical Society. Series A: Statistics in Society, vol. 185 no. 2 (April, 2022), pp. 588-614 [doi]  [abs]
  45. Van Den Boom, W; Reeves, G; Dunson, DB, Erratum: Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation (Biometrika (2021) 108 (269-282) DOI: 10.1093/biomet/asaa068), Biometrika, vol. 109 no. 1 (March, 2022), pp. 275 [doi]  [abs]
  46. Russo, M; Singer, BH; Dunson, DB, MULTIVARIATE MIXED MEMBERSHIP MODELING: INFERRING DOMAIN-SPECIFIC RISK PROFILES., The annals of applied statistics, vol. 16 no. 1 (March, 2022), pp. 391-413 [doi]  [abs]
  47. Joubert, BR; Kioumourtzoglou, M-A; Chamberlain, T; Chen, HY; Gennings, C; Turyk, ME; Miranda, ML; Webster, TF; Ensor, KB; Dunson, DB; Coull, BA, Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods., International journal of environmental research and public health, vol. 19 no. 3 (January, 2022), pp. 1378 [doi]  [abs]
  48. Peruzzi, M; Dunson, DB, Spatial Multivariate Trees for Big Data Bayesian Regression., Journal of machine learning research : JMLR, vol. 23 (January, 2022), pp. 17  [abs]
  49. Zhang, R; Mak, S; Dunson, D, GAUSSIAN PROCESS SUBSPACE PREDICTION FOR MODEL REDUCTION, SIAM Journal on Scientific Computing, vol. 44 no. 3 (January, 2022), pp. A1428-A1449 [doi]  [abs]
  50. Badea, A; Li, D; Niculescu, AR; Anderson, RJ; Stout, JA; Williams, CL; Colton, CA; Maeda, N; Dunson, DB, Corrigendum: Absolute winding number differentiates mouse spatial navigation strategies with genetic risk for Alzheimer's disease., Front Neurosci, vol. 16 (2022), pp. 1070425 [doi]  [abs]
  51. Badea, A; Li, D; Niculescu, AR; Anderson, RJ; Stout, JA; Williams, CL; Colton, CA; Maeda, N; Dunson, DB, Absolute Winding Number Differentiates Mouse Spatial Navigation Strategies With Genetic Risk for Alzheimer's Disease., Front Neurosci, vol. 16 (2022), pp. 848654 [doi]  [abs]
  52. Liu, M; Zhang, Z; Dunson, DB, Graph auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets., NeuroImage, vol. 245 (December, 2021), pp. 118750 [doi]  [abs]
  53. Dunson, DB; Wu, HT; Wu, N, Spectral convergence of graph Laplacian and heat kernel reconstruction in L∞ from random samples, Applied and Computational Harmonic Analysis, vol. 55 (November, 2021), pp. 282-336 [doi]  [abs]
  54. Moran, KR; Dunson, D; Wheeler, MW; Herring, AH, BAYESIAN JOINT MODELING OF CHEMICAL STRUCTURE AND DOSE RESPONSE CURVES., The annals of applied statistics, vol. 15 no. 3 (September, 2021), pp. 1405-1430 [doi]  [abs]
  55. Roy, A; Lavine, I; Herring, AH; Dunson, DB, PERTURBED FACTOR ANALYSIS: ACCOUNTING FOR GROUP DIFFERENCES IN EXPOSURE PROFILES., The annals of applied statistics, vol. 15 no. 3 (September, 2021), pp. 1386-1404 [doi]  [abs]
  56. Aliverti, E; Lum, K; Johndrow, JE; Dunson, DB, Removing the influence of group variables in high-dimensional predictive modelling., Journal of the Royal Statistical Society. Series A, (Statistics in Society), vol. 184 no. 3 (July, 2021), pp. 791-811 [doi]  [abs]
  57. Moran, KR; Turner, EL; Dunson, D; Herring, AH, Bayesian hierarchical factor regression models to infer cause of death from verbal autopsy data., J R Stat Soc Ser C Appl Stat, vol. 70 no. 3 (June, 2021), pp. 532-557 [doi]  [abs]
  58. VAN DEN Boom, W; Reeves, G; Dunson, DB, Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation., Biometrika, vol. 108 no. 2 (June, 2021), pp. 269-282 [doi]  [abs]
  59. Paganin, S; Herring, AH; Olshan, AF; Dunson, DB; National Birth Defects Prevention Study, Centered Partition Processes: Informative Priors for Clustering (with Discussion)., Bayesian analysis, vol. 16 no. 1 (March, 2021), pp. 301-370 [doi]  [abs]
  60. Ferrari, F; Dunson, DB, Bayesian Factor Analysis for Inference on Interactions., Journal of the American Statistical Association, vol. 116 no. 535 (January, 2021), pp. 1521-1532 [doi]  [abs]
  61. Jauch, M; Hoff, PD; Dunson, DB, Monte Carlo Simulation on the Stiefel Manifold via Polar Expansion, Journal of Computational and Graphical Statistics, vol. 30 no. 3 (January, 2021), pp. 622-631 [doi]  [abs]
  62. Lee, K; Lin, L; Dunson, D, Maximum pairwise bayes factors for covariance structure testing, Electronic Journal of Statistics, vol. 15 no. 2 (January, 2021), pp. 4384-4419 [doi]  [abs]
  63. Roy, A; Borg, JS; Dunson, DB, Bayesian time-aligned factor analysis of paired multivariate time series., Journal of machine learning research : JMLR, vol. 22 (January, 2021), pp. 250  [abs]
  64. Papadogeorgou, G; Zhang, Z; Dunson, DB, Soft tensor regression, Journal of Machine Learning Research, vol. 22 (January, 2021), pp. 1-53  [abs]
  65. Duan, LL; Dunson, DB, Bayesian Distance Clustering., Journal of machine learning research : JMLR, vol. 22 (January, 2021), pp. 224  [abs]
  66. Plummer, S; Zhou, S; Bhattacharya, A; Dunson, D; Pati, D, Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference, Proceedings of Machine Learning Research, vol. 130 (January, 2021), pp. 2449-2457  [abs]
  67. Mukhopadhyay, M; Li, D; Dunson, DB, Estimating densities with non-linear support by using Fisher-Gaussian kernels., Journal of the Royal Statistical Society. Series B, Statistical methodology, vol. 82 no. 5 (December, 2020), pp. 1249-1271 [doi]  [abs]
  68. Ferrari, F; Dunson, DB, IDENTIFYING MAIN EFFECTS AND INTERACTIONS AMONG EXPOSURES USING GAUSSIAN PROCESSES., The annals of applied statistics, vol. 14 no. 4 (December, 2020), pp. 1743-1758 [doi]  [abs]
  69. Li, D; Dunson, D, Classification via local manifold approximation, vol. 107 no. 4 (December, 2020), pp. 1013-1020 [doi]  [abs]
  70. Roy, A; Dunson, DB, Nonparametric graphical model for counts., Journal of machine learning research : JMLR, vol. 21 (December, 2020), pp. 229  [abs]
  71. Sen, D; Sachs, M; Lu, J; Dunson, DB, Efficient posterior sampling for high-dimensional imbalanced logistic regression., Biometrika, vol. 107 no. 4 (December, 2020), pp. 1005-1012 [doi]  [abs]
  72. Legramanti, S; Durante, D; Dunson, DB, Bayesian cumulative shrinkage for infinite factorizations., Biometrika, vol. 107 no. 3 (September, 2020), pp. 745-752 [doi]  [abs]
  73. Dunson, D; Papamarkou, T, Discussions, International Statistical Review, vol. 88 no. 2 (August, 2020), pp. 321-324 [doi]
  74. Binette, O; Pati, D; Dunson, DB, Bayesian closed surface fitting through tensor products, Journal of Machine Learning Research, vol. 21 (July, 2020), pp. 1-26  [abs]
  75. Aliverti, E; Tilson, JL; Filer, DL; Babcock, B; Colaneri, A; Ocasio, J; Gershon, TR; Wilhelmsen, KC; Dunson, DB, Projected t-SNE for batch correction., Bioinformatics (Oxford, England), vol. 36 no. 11 (June, 2020), pp. 3522-3527 [doi]  [abs]
  76. Nishimura, A; Dunson, DB; Lu, J, Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods, Biometrika, vol. 107 no. 2 (June, 2020), pp. 365-380 [doi]  [abs]
  77. Dunson, DB; Johndrow, JE, The Hastings algorithm at fifty, Biometrika, vol. 107 no. 1 (March, 2020), pp. 1-23 [doi]  [abs]
  78. Duan, LL; Young, AL; Nishimura, A; Dunson, DB, Bayesian constraint relaxation., Biometrika, vol. 107 no. 1 (March, 2020), pp. 191-204 [doi]  [abs]
  79. Tikhonov, G; Duan, L; Abrego, N; Newell, G; White, M; Dunson, D; Ovaskainen, O, Computationally efficient joint species distribution modeling of big spatial data., Ecology, vol. 101 no. 2 (February, 2020), pp. e02929 [doi]  [abs]
  80. Li, M; Dunson, DB, Comparing and weighting imperfect models using D-probabilities., Journal of the American Statistical Association, vol. 115 no. 531 (January, 2020), pp. 1349-1360 [doi]  [abs]
  81. Mukhopadhyay, M; Dunson, DB, Targeted Random Projection for Prediction From High-Dimensional Features, Journal of the American Statistical Association, vol. 115 no. 532 (January, 2020), pp. 1998-2010 [doi]  [abs]
  82. Jauch, M; Hoff, PD; Dunson, DB, Random orthogonal matrices and the Cayley transform, Bernoulli, vol. 26 no. 2 (January, 2020), pp. 1560-1586 [doi]  [abs]
  83. Nishimura, A; Dunson, D, Recycling Intermediate Steps to Improve Hamiltonian Monte Carlo, Bayesian Analysis, vol. 15 no. 4 (January, 2020), pp. 1087-1108 [doi]  [abs]
  84. Tam, E; Dunson, D, Fiedler regularization: Learning neural networks with graph sparsity, 37th International Conference on Machine Learning, ICML 2020, vol. PartF168147-12 (January, 2020), pp. 9288-9297, ISBN 9781713821120  [abs]
  85. Talbot, A; Dunson, D; Dzirasa, K; Carlson, D, Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity, arXiv preprint arXiv:2004.05209, vol. abs/2004.05209 (2020)
  86. Thai, DH; Wu, HT; Dunson, DB, Locally convex kernel mixtures: Bayesian subspace learning, Proceedings - 18th IEEE International Conference on Machine Learning and Applications, ICMLA 2019 (December, 2019), pp. 272-275, ISBN 9781728145495 [doi]  [abs]
  87. Camerlenghi, F; Dunson, DB; Lijoi, A; Prunster, I; Rodríguez, A, Latent nested nonparametric priors (with discussion), Bayesian Analysis, vol. 14 no. 4 (December, 2019), pp. 1303-1356, Institute of Mathematical Statistics [doi]  [abs]
  88. Panea, RI; Love, CL; Shingleton, JR; Reddy, A; Bailey, JA; Moormann, AM; Otieno, JA; Ong'echa, JM; Oduor, CI; Schroeder, KMS; Masalu, N; Chao, NJ; Agajanian, M; Major, MB; Fedoriw, Y; Richards, KL; Rymkiewicz, G; Miles, RR; Alobeid, B; Bhagat, G; Flowers, CR; Ondrejka, SL; Hsi, ED; Choi, WWL; Au-Yeung, RKH; Hartmann, W; Lenz, G; Meyerson, H; Lin, Y-Y; Zhuang, Y; Luftig, MA; Waldrop, A; Dave, T; Thakkar, D; Sahay, H; Li, G; Palus, BC; Seshadri, V; Kim, SY; Gascoyne, RD; Levy, S; Mukhopadyay, M; Dunson, DB; Dave, SS, The whole-genome landscape of Burkitt lymphoma subtypes., Blood, vol. 134 no. 19 (November, 2019), pp. 1598-1607 [doi]  [abs]
  89. Chae, M; Lin, L; Dunson, DB, Bayesian sparse linear regression with unknown symmetric error, Information and Inference, vol. 8 no. 3 (September, 2019), pp. 621-653 [doi]  [abs]
  90. Zhang, Z; Allen, GI; Zhu, H; Dunson, D, Tensor network factorizations: Relationships between brain structural connectomes and traits., NeuroImage, vol. 197 (August, 2019), pp. 330-343 [doi]  [abs]
  91. Norberg, A; Abrego, N; Blanchet, FG; Adler, FR; Anderson, BJ; Anttila, J; Araújo, MB; Dallas, T; Dunson, D; Elith, J; Foster, SD; Fox, R; Franklin, J; Godsoe, W; Guisan, A; O'Hara, B; Hill, NA; Holt, RD; Hui, FKC; Husby, M; Kålås, JA; Lehikoinen, A; Luoto, M; Mod, HK; Newell, G; Renner, I; Roslin, T; Soininen, J; Thuiller, W; Vanhatalo, J; Warton, D; White, M; Zimmermann, NE; Gravel, D; Ovaskainen, O, A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels, Ecological Monographs, vol. 89 no. 3 (August, 2019) [doi]  [abs]
  92. Johndrow, JE; Smith, A; Pillai, N; Dunson, DB, MCMC for Imbalanced Categorical Data, Journal of the American Statistical Association, vol. 114 no. 527 (July, 2019), pp. 1394-1403 [doi]  [abs]
  93. Niu, M; Cheung, P; Lin, L; Dai, Z; Lawrence, N; Dunson, D, Intrinsic Gaussian processes on complex constrained domains, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 81 no. 3 (July, 2019), pp. 603-627 [doi]  [abs]
  94. Wang, L; Zhang, Z; Dunson, D, Symmetric Bilinear Regression for Signal Subgraph Estimation., IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol. 67 no. 7 (April, 2019), pp. 1929-1940 [doi]  [abs]
  95. Dunson, D; Wood, S, Report of the Editors—2018, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 81 no. 1 (January, 2019), pp. 3-4 [doi]
  96. Miller, JW; Dunson, DB, Robust Bayesian inference via coarsening., Journal of the American Statistical Association, vol. 114 no. 527 (January, 2019), pp. 1113-1125, Informa UK Limited [doi]  [abs]
  97. Wang, L; Zhengwu Zhang; Dunson, COMMON AND INDIVIDUAL STRUCTURE OF MULTIPLE NETWORKS, vol. 13 no. 1 (January, 2019), pp. 85-112 [doi]  [abs]
  98. Zhang, Z; Descoteaux, M; Dunson, DB, Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions., Journal of the American Statistical Association, vol. 114 no. 528 (January, 2019), pp. 1505-1517 [doi]  [abs]
  99. Cheng, L; Lizhen, L; Dunson, DB, On posterior consistency of tail index for Bayesian kernel mixture models, Bernoulli, vol. 25 no. 3 (January, 2019), pp. 1999-2028, Bernoulli Society for Mathematical Statistics and Probability [doi]  [abs]
  100. Lin, L; Mu, N; Cheung, P; Dunson, D, Extrinsic Gaussian processes for regression and classification on manifolds, Bayesian Analysis, vol. 14 no. 3 (January, 2019), pp. 887-906 [doi]  [abs]
  101. Badea, A; Wu, W; Shuff, J; Wang, M; Anderson, RJ; Qi, Y; Johnson, GA; Wilson, JG; Koudoro, S; Garyfallidis, E; Colton, CA; Dunson, DB, Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer's Disease., Front Neuroinform, vol. 13 (2019), pp. 72 [doi]  [abs]
  102. Canale, A; Durante, D; Dunson, DB, Convex mixture regression for quantitative risk assessment., Biometrics, vol. 74 no. 4 (December, 2018), pp. 1331-1340 [doi]  [abs]
  103. Sarkar, A; Chabout, J; Macopson, JJ; Jarvis, ED; Dunson, DB, Bayesian Semiparametric Mixed Effects Markov Models With Application to Vocalization Syntax, Journal of the American Statistical Association, vol. 113 no. 524 (October, 2018), pp. 1515-1527, Informa UK Limited [doi]  [abs]
  104. Duan, LL; Johndrow, JE; Dunson, DB, Scaling up data augmentation MCMC via calibration, Journal of Machine Learning Research, vol. 19 (October, 2018)  [abs]
  105. Srivastava, S; Li, C; Dunson, DB, Scalable Bayes via barycenter in Wasserstein space, Journal of Machine Learning Research, vol. 19 (August, 2018), pp. 1-35  [abs]
  106. van den Boom, W; Mao, C; Schroeder, RA; Dunson, DB, Extrema-weighted feature extraction for functional data., Bioinformatics, vol. 34 no. 14 (July, 2018), pp. 2457-2464 [doi]  [abs]
  107. Guhaniyogi, R; Qamar, S; Dunson, DB, Bayesian Conditional Density Filtering, Journal of Computational and Graphical Statistics, vol. 27 no. 3 (July, 2018), pp. 657-672, Informa UK Limited [doi]  [abs]
  108. Shterev, ID; Dunson, DB; Chan, C; Sempowski, GD, Bayesian Multi-Plate High-Throughput Screening of Compounds., Sci Rep, vol. 8 no. 1 (June, 2018), pp. 9551 [doi]  [abs]
  109. Johndrow, JE; Lum, K; Dunson, DB, Theoretical limits of microclustering for record linkage., Biometrika, vol. 105 no. 2 (June, 2018), pp. 431-446 [doi]  [abs]
  110. Dunson, DB, Statistics in the big data era: Failures of the machine, Statistics and Probability Letters, vol. 136 (May, 2018), pp. 4-9, Elsevier BV [doi]  [abs]
  111. Zhang, Z; Descoteaux, M; Zhang, J; Girard, G; Chamberland, M; Dunson, D; Srivastava, A; Zhu, H, Mapping population-based structural connectomes., NeuroImage, vol. 172 (May, 2018), pp. 130-145 [doi]  [abs]
  112. van den Boom, W; Schroeder, RA; Manning, MW; Setji, TL; Fiestan, G-O; Dunson, DB, Effect of A1C and Glucose on Postoperative Mortality in Noncardiac and Cardiac Surgeries., Diabetes Care, vol. 41 no. 4 (April, 2018), pp. 782-788 [doi]  [abs]
  113. Durante, D; Dunson, DB, Supplementary Material For “Bayesian Inference And Testing Of Group Differences In Brain Networks”, Bayesian Analysis, vol. 13 no. 1 (January, 2018), pp. 1-2 [doi]  [abs]
  114. Bertrán, MA; Martínez, NL; Wang, Y; Dunson, D; Sapiro, G; Ringach, D, Active learning of cortical connectivity from two-photon imaging data., PloS one, vol. 13 no. 5 (January, 2018), pp. e0196527 [doi]  [abs]
  115. Durante, D; Dunson, DB, Bayesian inference and testing of group differences in brain networks, Bayesian Analysis, vol. 13 no. 1 (January, 2018), pp. 29-58, Institute of Mathematical Statistics [doi]  [abs]
  116. Zhao, S; Engelhardt, BE; Mukherjee, S; Dunson, DB, Fast Moment Estimation for Generalized Latent Dirichlet Models., Journal of the American Statistical Association, vol. 113 no. 524 (January, 2018), pp. 1528-1540 [doi]  [abs]
  117. Wheeler, MW; Dunson, DB; Herring, AH, Bayesian local extremum splines, Biometrika, vol. 104 no. 4 (December, 2017), pp. 939-952, Oxford University Press (OUP) [doi]  [abs]
  118. Minsker, S; Srivastava, S; Lin, L; Dunson, DB, Robust and scalable bayes via a median of subset posterior measures, Journal of Machine Learning Research, vol. 18 (December, 2017), pp. 1-40  [abs]
  119. Shang, Y; Dunson, D; Song, JS, Exploiting big data in logistics risk assessment via Bayesian nonparametrics, Operations Research, vol. 65 no. 6 (November, 2017), pp. 1574-1588, Institute for Operations Research and the Management Sciences (INFORMS) [doi]  [abs]
  120. Reddy, A; Zhang, J; Davis, NS; Moffitt, AB; Love, CL; Waldrop, A; Leppa, S; Pasanen, A; Meriranta, L; Karjalainen-Lindsberg, M-L; Nørgaard, P; Pedersen, M; Gang, AO; Høgdall, E; Heavican, TB; Lone, W; Iqbal, J; Qin, Q; Li, G; Kim, SY; Healy, J; Richards, KL; Fedoriw, Y; Bernal-Mizrachi, L; Koff, JL; Staton, AD; Flowers, CR; Paltiel, O; Goldschmidt, N; Calaminici, M; Clear, A; Gribben, J; Nguyen, E; Czader, MB; Ondrejka, SL; Collie, A; Hsi, ED; Tse, E; Au-Yeung, RKH; Kwong, Y-L; Srivastava, G; Choi, WWL; Evens, AM; Pilichowska, M; Sengar, M; Reddy, N; Li, S; Chadburn, A; Gordon, LI; Jaffe, ES; Levy, S; Rempel, R; Tzeng, T; Happ, LE; Dave, T; Rajagopalan, D; Datta, J; Dunson, DB; Dave, SS, Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma., Cell, vol. 171 no. 2 (October, 2017), pp. 481-494.e15 [doi]  [abs]
  121. Durante, D; Dunson, DB; Vogelstein, JT, Rejoinder: Nonparametric Bayes Modeling of Populations of Networks, Journal of the American Statistical Association, vol. 112 no. 520 (October, 2017), pp. 1547-1552, Informa UK Limited [doi]
  122. Durante, D; Dunson, DB; Vogelstein, JT, Nonparametric Bayes Modeling of Populations of Networks, Journal of the American Statistical Association, vol. 112 no. 520 (October, 2017), pp. 1516-1530, Informa UK Limited [doi]  [abs]
  123. Lock, EF; Dunson, DB, Bayesian genome- and epigenome-wide association studies with gene level dependence., Biometrics, vol. 73 no. 3 (September, 2017), pp. 1018-1028 [doi]  [abs]
  124. Li, C; Srivastava, S; Dunson, DB, Simple, scalable and accurate posterior interval estimation, Biometrika, vol. 104 no. 3 (September, 2017), pp. 665-680, Oxford University Press (OUP) [doi]  [abs]
  125. Srivastava, S; Engelhardt, BE; Dunson, DB, Expandable factor analysis., Biometrika, vol. 104 no. 3 (September, 2017), pp. 649-663 [doi]  [abs]
  126. Guhaniyogi, R; Qamar, S; Dunson, DB, Bayesian tensor regression, Journal of Machine Learning Research, vol. 18 (August, 2017), pp. 1-31  [abs]
  127. Schaich Borg, J; Srivastava, S; Lin, L; Heffner, J; Dunson, D; Dzirasa, K; de Lecea, L, Rat intersubjective decisions are encoded by frequency-specific oscillatory contexts., Brain Behav, vol. 7 no. 6 (June, 2017), pp. e00710 [doi]  [abs]
  128. Zhu, B; Dunson, DB, Bayesian functional data modeling for heterogeneous volatility, Bayesian Analysis, vol. 12 no. 2 (June, 2017), pp. 335-350, Institute of Mathematical Statistics [doi]  [abs]
  129. Wang, L; Durante, D; Jung, RE; Dunson, DB, Bayesian network-response regression., Bioinformatics (Oxford, England), vol. 33 no. 12 (June, 2017), pp. 1859-1866 [doi]  [abs]
  130. Rao, V; Adams, RP; Dunson, DD, Bayesian inference for Matérn repulsive processes, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 79 no. 3 (June, 2017), pp. 877-897 [doi]  [abs]
  131. Moffitt, AB; Ondrejka, SL; McKinney, M; Rempel, RE; Goodlad, JR; Teh, CH; Leppa, S; Mannisto, S; Kovanen, PE; Tse, E; Au-Yeung, RKH; Kwong, Y-L; Srivastava, G; Iqbal, J; Yu, J; Naresh, K; Villa, D; Gascoyne, RD; Said, J; Czader, MB; Chadburn, A; Richards, KL; Rajagopalan, D; Davis, NS; Smith, EC; Palus, BC; Tzeng, TJ; Healy, JA; Lugar, PL; Datta, J; Love, C; Levy, S; Dunson, DB; Zhuang, Y; Hsi, ED; Dave, SS, Enteropathy-associated T cell lymphoma subtypes are characterized by loss of function of SETD2., J Exp Med, vol. 214 no. 5 (May, 2017), pp. 1371-1386 [doi]  [abs]
  132. Ovaskainen, O; Tikhonov, G; Dunson, D; Grøtan, V; Engen, S; Sæther, B-E; Abrego, N, How are species interactions structured in species-rich communities? A new method for analysing time-series data., Proceedings. Biological sciences, vol. 284 no. 1855 (May, 2017), pp. 20170768 [doi]  [abs]
  133. Ovaskainen, O; Tikhonov, G; Norberg, A; Guillaume Blanchet, F; Duan, L; Dunson, D; Roslin, T; Abrego, N, How to make more out of community data? A conceptual framework and its implementation as models and software., Ecology letters, vol. 20 no. 5 (May, 2017), pp. 561-576 [doi]  [abs]
  134. Lin, L; Rao, V; Dunson, D, Bayesian nonparametric inference on the stiefel manifold, Statistica Sinica, vol. 27 no. 2 (April, 2017), pp. 535-553, Institute of Statistical Science [doi]  [abs]
  135. McKinney, M; Moffitt, AB; Gaulard, P; Travert, M; De Leval, L; Nicolae, A; Raffeld, M; Jaffe, ES; Pittaluga, S; Xi, L; Heavican, T; Iqbal, J; Belhadj, K; Delfau-Larue, MH; Fataccioli, V; Czader, MB; Lossos, IS; Chapman-Fredricks, JR; Richards, KL; Fedoriw, Y; Ondrejka, SL; Hsi, ED; Low, L; Weisenburger, D; Chan, WC; Mehta-Shah, N; Horwitz, S; Bernal-Mizrachi, L; Flowers, CR; Beaven, AW; Parihar, M; Baseggio, L; Parrens, M; Moreau, A; Sujobert, P; Pilichowska, M; Evens, AM; Chadburn, A; Au-Yeung, RKH; Srivastava, G; Choi, WWL; Goodlad, JR; Aurer, I; Basic-Kinda, S; Gascoyne, RD; Davis, NS; Li, G; Zhang, J; Rajagopalan, D; Reddy, A; Love, C; Levy, S; Zhuang, Y; Datta, J; Dunson, DB; Davé, SS, The Genetic Basis of Hepatosplenic T-cell Lymphoma., Cancer Discov, vol. 7 no. 4 (April, 2017), pp. 369-379 [doi]  [abs]
  136. Durante, D; Paganin, S; Scarpa, B; Dunson, DB, Bayesian modelling of networks in complex business intelligence problems, Journal of the Royal Statistical Society. Series C: Applied Statistics, vol. 66 no. 3 (April, 2017), pp. 555-580, WILEY [doi]  [abs]
  137. Tikhonov, G; Abrego, N; Dunson, D; Ovaskainen, O, Using joint species distribution models for evaluating how species-to-species associations depend on the environmental context, edited by Warton, D, Methods in Ecology and Evolution, vol. 8 no. 4 (April, 2017), pp. 443-452, WILEY [doi]  [abs]
  138. Dunson, DB, Toward automated prior choice, Statistical Science, vol. 32 no. 1 (February, 2017), pp. 41-43, Institute of Mathematical Statistics [doi]
  139. Abrego, N; Dunson, D; Halme, P; Salcedo, I; Ovaskainen, O, Wood-inhabiting fungi with tight associations with other species have declined as a response to forest management, Oikos, vol. 126 no. 2 (February, 2017), WILEY [doi]  [abs]
  140. Dunson, D; Fryzlewicz, P, Report of the editors-2016, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 79 no. 1 (January, 2017), pp. 3-4 [doi]
  141. Johndrow, JE; Bhattacharya, A; Dunson, DB, TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS., Annals of statistics, vol. 45 no. 1 (January, 2017), pp. 1-38 [doi]  [abs]
  142. Lin, L; St Thomas, B; Zhu, H; Dunson, DB, Extrinsic local regression on manifold-valued data., Journal of the American Statistical Association, vol. 112 no. 519 (January, 2017), pp. 1261-1273 [doi]  [abs]
  143. Datta, J; Dunson, DB, Bayesian inference on quasi-sparse count data., Biometrika, vol. 103 no. 4 (December, 2016), pp. 971-983 [doi]  [abs]
  144. Bhattacharya, A; Dunson, DB; Pati, D; Pillai, NS, Sub-optimality of some continuous shrinkage priors, Stochastic Processes and their Applications, vol. 126 no. 12 (December, 2016), pp. 3828-3842, Elsevier BV [doi]  [abs]
  145. Durante, D; Dunson, DB, Locally adaptive dynamic networks, Annals of Applied Statistics, vol. 10 no. 4 (December, 2016), pp. 2203-2232, Institute of Mathematical Statistics [doi]  [abs]
  146. Zhu, H; Strawn, N; Dunson, DB, Bayesian graphical models for multivariate functional data, Journal of Machine Learning Research, vol. 17 (October, 2016), pp. 1-27  [abs]
  147. Sarkar, A; Dunson, DB, Bayesian Nonparametric Modeling of Higher Order Markov Chains, Journal of the American Statistical Association, vol. 111 no. 516 (October, 2016), pp. 1791-1803, Informa UK Limited [doi]  [abs]
  148. Yin, R; Cornelis, B; Fodor, G; Ocon, N; Dunson, D; Daubechies, I, Removing cradle artifacts in X-ray images of paintings, SIAM Journal on Imaging Sciences, vol. 9 no. 3 (August, 2016), pp. 1247-1272, Society for Industrial & Applied Mathematics (SIAM) [doi]  [abs]
  149. Li, D; Heyer, L; Jennings, VH; Smith, CA; Dunson, DB, Personalised estimation of a woman's most fertile days., The European journal of contraception & reproductive health care : the official journal of the European Society of Contraception, vol. 21 no. 4 (August, 2016), pp. 323-328 [doi]  [abs]
  150. Hultman, R; Mague, SD; Li, Q; Katz, BM; Michel, N; Lin, L; Wang, J; David, LK; Blount, C; Chandy, R; Carlson, D; Ulrich, K; Carin, L; Dunson, D; Kumar, S; Deisseroth, K; Moore, SD; Dzirasa, K, Dysregulation of Prefrontal Cortex-Mediated Slow-Evolving Limbic Dynamics Drives Stress-Induced Emotional Pathology., Neuron, vol. 91 no. 2 (July, 2016), pp. 439-452 [doi]  [abs]
  151. Canale, A; Dunson, DB, Multiscale bernstein polynomials for densities, Statistica Sinica, vol. 26 no. 3 (July, 2016), pp. 1175-1195, Institute of Statistical Science [doi]  [abs]
  152. Kunihama, T; Herring, AH; Halpern, CT; Dunson, DB, Nonparametric Bayes modeling with sample survey weights., Statistics & probability letters, vol. 113 (June, 2016), pp. 41-48, Elsevier BV [doi]  [abs]
  153. Rao, V; Lin, L; Dunson, DB, Data augmentation for models based on rejection sampling., Biometrika, vol. 103 no. 2 (June, 2016), pp. 319-335 [doi]  [abs]
  154. Guhaniyogi, R; Dunson, DB, Compressed Gaussian process for manifold regression, Journal of Machine Learning Research, vol. 17 (May, 2016)  [abs]
  155. Ovaskainen, O; Abrego, N; Halme, P; Dunson, D, Using latent variable models to identify large networks of species-to-species associations at different spatial scales, edited by Warton, D, Methods in Ecology and Evolution, vol. 7 no. 5 (May, 2016), pp. 549-555, WILEY [doi]  [abs]
  156. Kabisa, S; Dunson, DB; Morris, JS, Online Variational Bayes Inference for High-Dimensional Correlated Data, Journal of Computational and Graphical Statistics, vol. 25 no. 2 (April, 2016), pp. 426-444, Informa UK Limited [doi]  [abs]
  157. Yang, Y; Dunson, DB, Bayesian manifold regression, Annals of Statistics, vol. 44 no. 2 (April, 2016), pp. 876-905, Institute of Mathematical Statistics [doi]  [abs]
  158. Zhou, J; Herring, AH; Bhattacharya, A; Olshan, AF; Dunson, DB; National Birth Defects Prevention Study, Nonparametric Bayes modeling for case control studies with many predictors., Biometrics, vol. 72 no. 1 (March, 2016), pp. 184-192 [doi]  [abs]
  159. Tang, K; Dunson, DB; Su, Z; Liu, R; Zhang, J; Dong, J, Subspace segmentation by dense block and sparse representation., Neural networks : the official journal of the International Neural Network Society, vol. 75 (March, 2016), pp. 66-76 [doi]  [abs]
  160. Wang, X; Dunson, D; Leng, C, No penalty no tears: Least squares in high-dimensional linear models, 33rd International Conference on Machine Learning, ICML 2016, vol. 4 (January, 2016), pp. 2685-2706, ISBN 9781510829008  [abs]
  161. Wang, X; Dunson, D; Leng, C, DECOrrelated feature space partitioning for distributed sparse regression, Advances in Neural Information Processing Systems (January, 2016), pp. 802-810  [abs]
  162. Yang, Y; Dunson, DB, Bayesian Conditional Tensor Factorizations for High-Dimensional Classification., Journal of the American Statistical Association, vol. 111 no. 514 (January, 2016), pp. 656-669, Informa UK Limited [doi]  [abs]
  163. Wang, Y; Canale, A; Dunson, D, Scalable geometric density estimation, Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016 (January, 2016), pp. 857-865  [abs]
  164. Han, S; Liao, X; Dunson, DB; Carin, L, Variational Gaussian copula inference, Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016 (January, 2016), pp. 829-838  [abs]
  165. Chabout, J; Sarkar, A; Patel, SR; Radden, T; Dunson, DB; Fisher, SE; Jarvis, ED, A Foxp2 Mutation Implicated in Human Speech Deficits Alters Sequencing of Ultrasonic Vocalizations in Adult Male Mice., Front Behav Neurosci, vol. 10 (2016), pp. 197 [doi]  [abs]
  166. Fox, EB; Dunson, DB; Airoldi, EM, Bayesian nonparametric covariance regression, Journal of Machine Learning Research, vol. 16 (December, 2015), pp. 2501-2542  [abs]
  167. Yazdani, A; Dunson, DB, A hybrid bayesian approach for genome-wide association studies on related individuals., Bioinformatics (Oxford, England), vol. 31 no. 24 (December, 2015), pp. 3890-3896 [doi]  [abs]
  168. Lock, EF; Dunson, DB, Shared kernel Bayesian screening., Biometrika, vol. 102 no. 4 (December, 2015), pp. 829-842 [doi]  [abs]
  169. Bhattacharya, A; Pati, D; Pillai, NS; Dunson, DB, Dirichlet-Laplace priors for optimal shrinkage., Journal of the American Statistical Association, vol. 110 no. 512 (December, 2015), pp. 1479-1490 [doi]  [abs]
  170. Guhaniyogi, R; Dunson, DB, Bayesian Compressed Regression, Journal of the American Statistical Association, vol. 110 no. 512 (October, 2015), pp. 1500-1514, Informa UK Limited [doi]  [abs]
  171. Guo, F; Dunson, DB, Uncovering systematic bias in ratings across categories: A Bayesian approach, RecSys 2015 - Proceedings of the 9th ACM Conference on Recommender Systems (September, 2015), pp. 317-320, ISBN 9781450336925 [doi]  [abs]
  172. Johndrow, JE; Mattingly, JC; Mukherjee, S; Dunson, D, Optimal approximating Markov chains for Bayesian inference (August, 2015)  [abs]
  173. Hua, Z; Zhu, H; Dunson, DB, Semiparametric Bayes local additive models for longitudinal data., Statistics in biosciences, vol. 7 no. 1 (May, 2015), pp. 90-107, ISSN 1867-1764 [doi]  [abs]
  174. Li, D; Wilcox, AJ; Dunson, DB, Benchmark pregnancy rates and the assessment of post-coital contraceptives: an update., Contraception, vol. 91 no. 4 (April, 2015), pp. 344-349, ISSN 0010-7824 [doi]  [abs]
  175. Strawn, N; Armagan, A; Saab, R; Carin, L; Dunson, D, Erratum: Finite sample posterior concentration in high-dimensional regression (Information and Inference (2015) 3 (103-133) DOI: 10.1093/imaiai/iau003), Information and Inference, vol. 4 no. 1 (March, 2015), pp. 77 [doi]  [abs]
  176. Lock, EF; Soldano, KL; Garrett, ME; Cope, H; Markunas, CA; Fuchs, H; Grant, G; Dunson, DB; Gregory, SG; Ashley-Koch, AE, Joint eQTL assessment of whole blood and dura mater tissue from individuals with Chiari type I malformation., BMC Genomics, vol. 16 no. 1 (January, 2015), pp. 11 [doi]  [abs]
  177. Canale, A; Dunson, DB, Bayesian multivariate mixed-scale density estimation, Statistics and its Interface, vol. 8 no. 2 (January, 2015), pp. 195-201, International Press of Boston, ISSN 1938-7989 [doi]  [abs]
  178. Kessler, DC; Hoff, PD; Dunson, DB, Marginally specified priors for non-parametric Bayesian estimation., Journal of the Royal Statistical Society. Series B, Statistical methodology, vol. 77 no. 1 (January, 2015), pp. 35-58, ISSN 1369-7412 [doi]  [abs]
  179. Wang, X; Guo, F; Heller, KA; Dunson, DB, Parallelizing MCMC with random partition trees, Advances in Neural Information Processing Systems, vol. 2015-January (January, 2015), pp. 451-459  [abs]
  180. Kunihama, T; Dunson, DB, Nonparametric Bayes inference on conditional independence, Biometrika, vol. 103 no. 1 (January, 2015), pp. 35-47, Oxford University Press (OUP) [doi]  [abs]
  181. Van Den Boom, W; Dunson, D; Reeves, G, Quantifying uncertainty in variable selection with arbitrary matrices, 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015 (January, 2015), pp. 385-388, ISBN 9781479919635 [doi]  [abs]
  182. Zhou, J; Bhattacharya, A; Herring, A; Dunson, D, Bayesian factorizations of big sparse tensors., Journal of the American Statistical Association, vol. 110 no. 512 (January, 2015), pp. 1562-1576, Informa UK Limited [doi]  [abs]
  183. Srivastava, S; Cevher, V; Tran-Dinh, Q; Dunson, DB, WASP: Scalable Bayes via barycenters of subset posteriors, Journal of Machine Learning Research, vol. 38 (January, 2015), pp. 912-920  [abs]
  184. Wang, X; Leng, C; Dunson, DB, On the consistency theory of high dimensional variable screening, Advances in Neural Information Processing Systems, vol. 2015-January (January, 2015), pp. 2431-2439  [abs]
  185. Wang, Y; Dunson, D, Probabilistic curve learning: Coulomb repulsion and the electrostatic Gaussian process, Advances in Neural Information Processing Systems, vol. 2015-January (January, 2015), pp. 1738-1746  [abs]
  186. Chabout, J; Sarkar, A; Dunson, DB; Jarvis, ED, Male mice song syntax depends on social contexts and influences female preferences., Front Behav Neurosci, vol. 9 (2015), pp. 76, FRONTIERS MEDIA SA [repository], [doi]  [abs]
  187. Durante, D; Dunson, DB, Nonparametric Bayes dynamic modelling of relational data, Biometrika, vol. 101 no. 4 (December, 2014), pp. 883-898, Oxford University Press (OUP) [doi]  [abs]
  188. Yang, H; Liu, F; Ji, C; Dunson, D, Adaptive sampling for Bayesian geospatial models, Statistics and Computing, vol. 24 no. 6 (November, 2014), pp. 1101-1110, Springer Nature, ISSN 0960-3174 [doi]  [abs]
  189. Gu, K; Pati, D; Dunson, DB, Bayesian Multiscale Modeling of Closed Curves in Point Clouds., Journal of the American Statistical Association, vol. 109 no. 508 (October, 2014), pp. 1481-1494, ISSN 0162-1459 [doi]  [abs]
  190. Rodriguez, A; Dunson, DB, Functional clustering in nested designs: Modeling variability in reproductive epidemiology studies, Annals of Applied Statistics, vol. 8 no. 3 (September, 2014), pp. 1416-1442, Institute of Mathematical Statistics, ISSN 1932-6157 [doi]  [abs]
  191. Dunson, DB, Comment, Journal of the American Statistical Association, vol. 109 no. 507 (July, 2014), pp. 890-891, Informa UK Limited, ISSN 0162-1459 [doi]
  192. Wheeler, MW; Dunson, DB; Pandalai, SP; Baker, BA; Herring, AH, Mechanistic Hierarchical Gaussian Processes., Journal of the American Statistical Association, vol. 109 no. 507 (July, 2014), pp. 894-904, ISSN 0162-1459 [doi]  [abs]
  193. Kessler, DC; Taylor, JA; Dunson, DB, Learning phenotype densities conditional on many interacting predictors., Bioinformatics (Oxford, England), vol. 30 no. 11 (June, 2014), pp. 1562-1568, ISSN 1367-4803 [doi]  [abs]
  194. Strawn, N; Armagan, A; Saab, R; Carin, L; Dunson, D, Finite sample posterior concentration in high-dimensional regression, Information and Inference, vol. 3 no. 2 (June, 2014), pp. 103-133 [doi]  [abs]
  195. Zhang, J; Jima, D; Moffitt, AB; Liu, Q; Czader, M; Hsi, ED; Fedoriw, Y; Dunphy, CH; Richards, KL; Gill, JI; Sun, Z; Love, C; Scotland, P; Lock, E; Levy, S; Hsu, DS; Dunson, D; Dave, SS, The genomic landscape of mantle cell lymphoma is related to the epigenetically determined chromatin state of normal B cells., Blood, vol. 123 no. 19 (May, 2014), pp. 2988-2996, ISSN 0006-4971 [doi]  [abs]
  196. Kundu, S; Dunson, DB, Bayes variable selection in semiparametric linear models., Journal of the American Statistical Association, vol. 109 no. 505 (March, 2014), pp. 437-447, ISSN 0162-1459 [doi]  [abs]
  197. Cui, K; Dunson, DB, Generalized Dynamic Factor Models for Mixed-Measurement Time Series., Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, vol. 23 no. 1 (February, 2014), pp. 169-191, ISSN 1061-8600 [doi]  [abs]
  198. Pati, D; Dunson, DB, Bayesian nonparametric regression with varying residual density., Annals of the Institute of Statistical Mathematics, vol. 66 no. 1 (February, 2014), pp. 1-31, ISSN 0020-3157 [doi]  [abs]
  199. Yin, R; Dunson, D; Cornelis, B; Brown, B; Ocon, N; Daubechies, I, Digital cradle removal in X-ray images of art paintings, 2014 IEEE International Conference on Image Processing, ICIP 2014 (January, 2014), pp. 4299-4303, IEEE, ISBN 9781479957514 [doi]  [abs]
  200. Durante, D; Dunson, DB, Bayesian dynamic financial networks with time-varying predictors, Statistics and Probability Letters, vol. 93 (January, 2014), pp. 19-26, Elsevier BV, ISSN 0167-7152 [doi]  [abs]
  201. Chen, CWS; Dunson, D; Frühwirth-Schnatter, S; Walker, SG, Special issue on Bayesian computing, methods and applications, Computational Statistics and Data Analysis, vol. 71 (January, 2014), pp. 273, Elsevier BV, ISSN 0167-9473 [doi]
  202. Rai, P; Wang, Y; Guo, S; Chen, G; Dunson, D; Carin, L, Scalable bayesian low-rank decomposition of incomplete multiway tensors, 31st International Conference on Machine Learning, ICML 2014, vol. 5 (January, 2014), pp. 3810-3820, ISBN 9781634393973  [abs]
  203. Wang, X; Peng, P; Dunson, DB, Median selection subset aggregation for parallel inference, Advances in Neural Information Processing Systems, vol. 3 no. January (January, 2014), pp. 2195-2203, ISSN 1049-5258  [abs]
  204. Minsker, S; Srivastava, S; Lin, L; Dunson, DB, Scalable and robust Bayesian inference via the median posterior, 31st International Conference on Machine Learning, ICML 2014, vol. 5 (January, 2014), pp. 3629-3639, ISBN 9781634393973  [abs]
  205. Kundu, S; Dunson, DB, Latent factor models for density estimation, Biometrika, vol. 101 no. 3 (January, 2014), pp. 641-654, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  206. Hannah, LA; Powell, WB; Dunson, DB, Semiconvex regression for metamodeling-based optimization, SIAM Journal on Optimization, vol. 24 no. 2 (January, 2014), pp. 573-597, Society for Industrial & Applied Mathematics (SIAM), ISSN 1052-6234 [doi]  [abs]
  207. Pati, D; Bhattacharya, A; Pillai, NS; Dunson, D, Posterior contraction in sparse bayesian factor models for massive covariance matrices, Annals of Statistics, vol. 42 no. 3 (January, 2014), pp. 1102-1130, Institute of Mathematical Statistics, ISSN 0090-5364 [doi]  [abs]
  208. Durante, D; Scarpa, B; Dunson, DB, Locally adaptive factor processes for multivariate time series, Journal of Machine Learning Research, vol. 15 (January, 2014), pp. 1493-1522, ISSN 1532-4435  [abs]
  209. Lin, L; Dunson, DB, Bayesian monotone regression using Gaussian process projection, Biometrika, vol. 101 no. 2 (January, 2014), pp. 303-317, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  210. Xing, Z; Nicholson, B; Jimenez, M; Veldman, T; Hudson, L; Lucas, J; Dunson, D; Zaas, AK; Woods, CW; Ginsburg, GS; Carin, L, Bayesian modeling of temporal properties of infectious disease in a college student population, Journal of Applied Statistics, vol. 41 no. 6 (January, 2014), pp. 1358-1382, ISSN 0266-4763 [doi]  [abs]
  211. Wade, S; Dunson, DB; Petrone, S; Trippa, L, Improving prediction from dirichlet process mixtures via enrichment, Journal of Machine Learning Research, vol. 15 (January, 2014), pp. 1041-1071, ISSN 1532-4435  [abs]
  212. Bhattacharya, A; Pati, D; Dunson, D, Anisotropic function estimation using multi-bandwidth Gaussian processes, Annals of Statistics, vol. 42 no. 1 (January, 2014), pp. 352-381, Institute of Mathematical Statistics [doi]  [abs]
  213. Durante, D; Dunson, DB, Bayesian logistic Gaussian process models for dynamic networks, Journal of Machine Learning Research, vol. 33 (January, 2014), pp. 194-201  [abs]
  214. Scarpa, B; Dunson, DB, Enriched Stick Breaking Processes for Functional Data., Journal of the American Statistical Association, vol. 109 no. 506 (January, 2014), pp. 647-660 [doi]  [abs]
  215. Cornelis, B; Yang, Y; Vogelstein, JT; Dooms, A; Daubechies, I; Dunson, D, Bayesian crack detection in ultra high resolution multimodal images of paintings, 2013 18th International Conference on Digital Signal Processing, DSP 2013 (December, 2013) [1304.5894v2], [doi]  [abs]
  216. Armagan, A; Dunson, DB; Lee, J; Bajwa, WU; Strawn, N, Posterior consistency in linear models under shrinkage priors, Biometrika, vol. 100 no. 4 (December, 2013), pp. 1011-1018, Oxford University Press (OUP), ISSN 0006-3444 [Gateway.cgi], [doi]  [abs]
  217. Canale, A; Dunson, DB, Nonparametric Bayes modelling of count processes, Biometrika, vol. 100 no. 4 (December, 2013), pp. 801-816, Oxford University Press (OUP), ISSN 0006-3444 [Gateway.cgi], [doi]  [abs]
  218. Hannah, LA; Dunson, DB, Multivariate Convex Regression with Adaptive Partitioning, JOURNAL OF MACHINE LEARNING RESEARCH, vol. 14 (November, 2013), pp. 3261-3294, MICROTOME PUBL
  219. Hannah, LA; Dunson, DB, Multivariate convex regression with adaptive partitioning, Journal of Machine Learning Research, vol. 14 (November, 2013), pp. 3153-3188, MICROTOME PUBL, ISSN 1532-4435  [abs]
  220. Li, D; Longnecker, MP; Dunson, DB, Lipid adjustment for chemical exposures: accounting for concomitant variables., Epidemiology (Cambridge, Mass.), vol. 24 no. 6 (November, 2013), pp. 921-928 [24051893], [doi]  [abs]
  221. Lock, EF; Dunson, DB, Bayesian consensus clustering., Bioinformatics (Oxford, England), vol. 29 no. 20 (October, 2013), pp. 2610-2616 [23990412], [doi]  [abs]
  222. Salazar, E; Dunson, DB; Carin, L, Analysis of space-time relational data with application to legislative voting, Computational Statistics and Data Analysis, vol. 68 (July, 2013), pp. 141-154, Elsevier BV, ISSN 0167-9473 [doi]  [abs]
  223. Zhu, B; Ashley-Koch, AE; Dunson, DB, Generalized admixture mapping for complex traits., G3 (Bethesda), vol. 3 no. 7 (July, 2013), pp. 1165-1175 [23665878], [doi]  [abs]
  224. Murray, JS; Dunson, DB; Carin, L; Lucas, JE, Bayesian Gaussian Copula Factor Models for Mixed Data., Journal of the American Statistical Association, vol. 108 no. 502 (June, 2013), pp. 656-665 [1111.0317v2], [doi]  [abs]
  225. Page, G; Bhattacharya, A; Dunson, D, Classification via bayesian nonparametric learning of affine subspaces, Journal of the American Statistical Association, vol. 108 no. 501 (May, 2013), pp. 187-201, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  226. Pati, D; Dunson, DB; Tokdar, ST, Posterior consistency in conditional distribution estimation., Journal of multivariate analysis, vol. 116 (April, 2013), pp. 456-472, ISSN 0047-259X [doi]  [abs]
  227. Wang, E; Salazar, E; Dunson, D; Carin, L, Spatio-temporal modeling of legislation and votes, Bayesian Analysis, vol. 8 no. 1 (March, 2013), pp. 233-268, Institute of Mathematical Statistics, ISSN 1936-0975 [doi]  [abs]
  228. Zhang, J; Grubor, V; Love, CL; Banerjee, A; Richards, KL; Mieczkowski, PA; Dunphy, C; Choi, W; Au, WY; Srivastava, G; Lugar, PL; Rizzieri, DA; Lagoo, AS; Bernal-Mizrachi, L; Mann, KP; Flowers, C; Naresh, K; Evens, A; Gordon, LI; Czader, M; Gill, JI; Hsi, ED; Liu, Q; Fan, A; Walsh, K; Jima, D; Smith, LL; Johnson, AJ; Byrd, JC; Luftig, MA; Ni, T; Zhu, J; Chadburn, A; Levy, S; Dunson, D; Dave, SS, Genetic heterogeneity of diffuse large B-cell lymphoma., Proc Natl Acad Sci U S A, vol. 110 no. 4 (January, 2013), pp. 1398-1403 [23292937], [doi]  [abs]
  229. Petralia, F; Vogelstein, J; Dunson, DB, Multiscale dictionary learning for estimating conditional distributions, Advances in Neural Information Processing Systems (January, 2013), ISSN 1049-5258  [abs]
  230. Durante, D; Scarpa, B; Dunson, DB, Locally adaptive bayesian multivariate time series, Advances in Neural Information Processing Systems (January, 2013), ISSN 1049-5258  [abs]
  231. Zhu, B; Dunson, DB, Locally Adaptive Bayes Nonparametric Regression via Nested Gaussian Processes., Journal of the American Statistical Association, vol. 108 no. 504 (January, 2013), ISSN 0162-1459 [doi]  [abs]
  232. Kunihama, T; Dunson, DB, Bayesian modeling of temporal dependence in large sparse contingency tables., Journal of the American Statistical Association, vol. 108 no. 504 (January, 2013), pp. 1324-1338, ISSN 0162-1459 [doi]  [abs]
  233. Armagan, A; Dunson, DB; Lee, J, GENERALIZED DOUBLE PARETO SHRINKAGE., Statistica Sinica, vol. 23 no. 1 (January, 2013), pp. 119-143, ISSN 1017-0405 [doi]  [abs]
  234. Chen, B; Polatkan, G; Sapiro, G; Blei, D; Dunson, D; Carin, L, Deep Learning with Hierarchical Convolutional Factor Analysis., IEEE transactions on pattern analysis and machine intelligence (January, 2013) [23319498]  [abs]
  235. Yu, K; Chen, CWS; Reed, C; Dunson, DB, Bayesian variable selection in quantile regression, Statistics and its Interface, vol. 6 no. 2 (January, 2013), pp. 261-274, International Press of Boston, ISSN 1938-7989 [Gateway.cgi], [doi]  [abs]
  236. Johndrow, JE; Lum, K; Dunson, DB, Diagonal orthant multinomial probit models, Journal of Machine Learning Research, vol. 31 (January, 2013), pp. 29-38  [abs]
  237. Banerjee, A; Murray, J; Dunson, DB, Bayesian learning of joint distributions of objects, Journal of Machine Learning Research, vol. 31 (January, 2013), pp. 1-9  [abs]
  238. Xing, Z; Nicholson, B; Jimenez, M; Veldman, T; Hudson, L; Lucas, J; Dunson, D; Zaas, AK; Woods, CW; Ginsburg, GS; Carin, L, Bayesian modeling of temporal properties of infectious disease in a college student population, Journal of Applied Statistics, vol. 41 no. 6 (2013), pp. 1358-1382, Informa UK Limited, ISSN 0266-4763 [doi]
  239. Carlson, DE; Vogelstein, JT; Wu, Q; Lian, W; Zhou, M; Stoetzner, CR; Kipke, D; Weber, D; Dunson, DB; Carin, L, Multichannel electrophysiological spike sorting via joint dictionary learning and mixture modeling, IEEE Transactions on Biomedical Engineering, vol. 61 no. 1 (2013), pp. 41-54, IEEE, ISSN 0018-9294 [doi]  [abs]
  240. Banerjee, A; Dunson, DB; Tokdar, ST, Efficient Gaussian process regression for large datasets, Biometrika, vol. 100 no. 1 (2013), pp. 75-89 [1106.5779v1], [doi]  [abs]
  241. Zhu, B; Dunson, DB; Ashley-Koch, AE, Adverse subpopulation regression for multivariate outcomes with high-dimensional predictors., Stat Med, vol. 31 no. 29 (December, 2012), pp. 4102-4113 [22825854], [doi]  [abs]
  242. Petralia, F; Rao, V; Dunson, DB, Repulsive mixtures, Advances in Neural Information Processing Systems, vol. 3 (December, 2012), pp. 1889-1897, ISSN 1049-5258  [abs]
  243. Fox, EB; Dunson, DB, Multiresolution Gaussian processes, Advances in Neural Information Processing Systems, vol. 1 (December, 2012), pp. 737-745, ISSN 1049-5258  [abs]
  244. Ding, M; He, L; Dunson, D; Carin, L, Nonparametric Bayesian Segmentation of a Multivariate Inhomogeneous Space-Time Poisson Process., Bayesian analysis, vol. 7 no. 4 (December, 2012), pp. 813-840, ISSN 1931-6690 [Gateway.cgi], [doi]  [abs]
  245. Love, C; Sun, Z; Jima, D; Li, G; Zhang, J; Miles, R; Richards, KL; Dunphy, CH; Choi, WWL; Srivastava, G; Lugar, PL; Rizzieri, DA; Lagoo, AS; Bernal-Mizrachi, L; Mann, KP; Flowers, CR; Naresh, KN; Evens, AM; Chadburn, A; Gordon, LI; Czader, MB; Gill, JI; Hsi, ED; Greenough, A; Moffitt, AB; McKinney, M; Banerjee, A; Grubor, V; Levy, S; Dunson, DB; Dave, SS, The genetic landscape of mutations in Burkitt lymphoma., Nat Genet, vol. 44 no. 12 (December, 2012), pp. 1321-1325 [23143597], [doi]  [abs]
  246. Montagna, S; Tokdar, ST; Neelon, B; Dunson, DB, Bayesian latent factor regression for functional and longitudinal data., Biometrics, vol. 68 no. 4 (December, 2012), pp. 1064-1073 [23005895], [doi]  [abs]
  247. Hannah, LA; Dunson, DB, Ensemble methods for convex regression with applications to geometric programming based circuit design, Proceedings of the 29th International Conference on Machine Learning, ICML 2012, vol. 1 (October, 2012), pp. 369-376  [abs]
  248. Shterev, ID; Dunson, DB, Bayesian watermark attacks, Proceedings of the 29th International Conference on Machine Learning, ICML 2012, vol. 1 (October, 2012), pp. 695-702  [abs]
  249. Zhou, M; Li, L; Dunson, D; Carin, L, Lognormal and gamma mixed negative binomial regression, Proceedings of the 29th International Conference on Machine Learning, ICML 2012, vol. 2 (October, 2012), pp. 1343-1350 [repository]  [abs]
  250. Bhattacharya, A; Dunson, D, Nonparametric Bayes classification and hypothesis testing on manifolds, Journal of Multivariate Analysis, vol. 111 (October, 2012), pp. 1-19, Elsevier BV, ISSN 0047-259X [doi]  [abs]
  251. Hua, Z; Dunson, DB; Gilmore, JH; Styner, MA; Zhu, H, Semiparametric Bayesian local functional models for diffusion tensor tract statistics., NeuroImage, vol. 63 no. 1 (October, 2012), pp. 460-474, ISSN 1053-8119 [doi]  [abs]
  252. Bhattacharya, A; Dunson, DB, Strong consistency of nonparametric Bayes density estimation on compact metric spaces with applications to specific manifolds., Annals of the Institute of Statistical Mathematics, vol. 64 no. 4 (August, 2012), pp. 687-714, ISSN 0020-3157 [doi]  [abs]
  253. Bhattacharya, A; Dunson, DB, Simplex Factor Models for Multivariate Unordered Categorical Data., Journal of the American Statistical Association, vol. 107 no. 497 (March, 2012), pp. 362-377, ISSN 0162-1459 [doi]  [abs]
  254. Carin, L; Hero, A; Lucas, J; Dunson, D; Chen, M; Heñao, R; Tibau-Puig, A; Zaas, A; Woods, CW; Ginsburg, GS, High-Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections., IEEE Signal Process Mag, vol. 29 no. 1 (January, 2012), pp. 108-123 [doi]
  255. Zhou, M; Chen, H; Paisley, J; Ren, L; Li, L; Xing, Z; Dunson, D; Sapiro, G; Carin, L, Nonparametric Bayesian dictionary learning for analysis of noisy and incomplete images., IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, vol. 21 no. 1 (January, 2012), pp. 130-144 [21693421], [doi]  [abs]
  256. Dunson, DB; Xing, C, Nonparametric Bayes Modeling of Multivariate Categorical Data., Journal of the American Statistical Association, vol. 104 no. 487 (January, 2012), pp. 1042-1051, ISSN 0162-1459 [doi]  [abs]
  257. Fyshe, A; Fox, E; Dunson, D; Mitchell, T, Hierarchical latent dictionaries for models of brain activation, Journal of Machine Learning Research, vol. 22 (January, 2012), pp. 409-421  [abs]
  258. Zhou, M; Hannah, LA; Dunson, DB; Carin, L, Beta-negative binomial process and poisson factor analysis, Journal of Machine Learning Research, vol. 22 (January, 2012), pp. 1462-1471  [abs]
  259. Gordon, GJ; Dunson, D, Preface to the proceedings of AISTATS 2011, Journal of Machine Learning Research, vol. 15 (December, 2011), pp. 1-2, ISSN 1532-4435
  260. Canale, A; Dunson, DB, Bayesian Kernel Mixtures for Counts., Journal of the American Statistical Association, vol. 106 no. 496 (December, 2011), pp. 1528-1539, ISSN 0162-1459 [doi]  [abs]
  261. Zhang, XX; Dunson, DB; Carin, L, Hierarchical topic modeling for analysis of time-evolving personal choices, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 (December, 2011)  [abs]
  262. Ren, L; Wang, Y; Dunson, D; Carin, L, The kernel beta process, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 (December, 2011)  [abs]
  263. Zhou, M; Carin, L; Yang, H; Dunson, D; Sapiro, G, Dependent hierarchical beta process for image interpolation and denoising, Journal of Machine Learning Research, vol. 15 (December, 2011), pp. 883-891, ISSN 1532-4435  [abs]
  264. Hannah, LA; Dunson, DB, Approximate dynamic programming for storage problems, Proceedings of the 28th International Conference on Machine Learning, ICML 2011 (October, 2011), pp. 337-344  [abs]
  265. Chen, B; Polatkan, G; Sapiro, G; Dunson, DB; Carin, L, The hierarchical beta process for convolutional factor analysis and deep learning, Proceedings of the 28th International Conference on Machine Learning, ICML 2011 (October, 2011), pp. 361-368  [abs]
  266. Yang, H; O'Brien, S; Dunson, DB, Nonparametric Bayes Stochastically Ordered Latent Class Models., J Am Stat Assoc, vol. 106 no. 495 (September, 2011), pp. 807-817, ISSN 0162-1459 [22505787], [doi]  [abs]
  267. Wang, L; Dunson, DB, Semiparametric bayes' proportional odds models for current status data with underreporting., Biometrics, vol. 67 no. 3 (September, 2011), pp. 1111-1118, ISSN 0006-341X [doi]  [abs]
  268. Wang, L; Dunson, DB, Bayesian isotonic density regression., Biometrika, vol. 98 no. 3 (September, 2011), pp. 537-551, ISSN 0006-3444 [doi]  [abs]
  269. Zhou, M; Yang, H; Sapiro, G; Dunson, D; Carin, L, Covariate-dependent dictionary learning and sparse coding, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (August, 2011), pp. 5824-5827, IEEE, ISSN 1520-6149 [doi]  [abs]
  270. Armagan, A; Dunson, D, Sparse variational analysis of linear mixed models for large data sets, Statistics and Probability Letters, vol. 81 no. 8 (August, 2011), pp. 1056-1062, Elsevier BV, ISSN 0167-7152 [doi]  [abs]
  271. Xing, C; Dunson, DB, Bayesian inference for genomic data integration reduces misclassification rate in predicting protein-protein interactions., PLoS computational biology, vol. 7 no. 7 (July, 2011), pp. e1002110 [21829334], [doi]  [abs]
  272. Bhattacharya, A; Dunson, DB, Sparse Bayesian infinite factor models., Biometrika, vol. 98 no. 2 (June, 2011), pp. 291-306, ISSN 0006-3444 [23049129], [doi]  [abs]
  273. Liu, F; Dunson, D; Zou, F, High-dimensional variable selection in meta-analysis for censored data., Biometrics, vol. 67 no. 2 (June, 2011), pp. 504-512, ISSN 0006-341X [doi]  [abs]
  274. Page, GL; Dunson, DB, Bayesian Local Contamination Models for Multivariate Outliers., Technometrics : a journal of statistics for the physical, chemical, and engineering sciences, vol. 53 no. 2 (May, 2011), pp. 152-162, ISSN 0040-1706 [doi]  [abs]
  275. Crandell, JL; Dunson, DB, Posterior simulation across nonparametric models for functional clustering, Sankhya B, vol. 73 no. 1 (May, 2011), pp. 42-61, Springer Nature, ISSN 0972-7671 [doi]  [abs]
  276. Dzirasa, K; McGarity, DL; Bhattacharya, A; Kumar, S; Takahashi, JS; Dunson, D; McClung, CA; Nicolelis, MAL, Impaired limbic gamma oscillatory synchrony during anxiety-related behavior in a genetic mouse model of bipolar mania., J Neurosci, vol. 31 no. 17 (April, 2011), pp. 6449-6456 [21525286], [doi]  [abs]
  277. Rodríguez, A; Dunson, DB, Nonparametric Bayesian models through probit stick-breaking processes., Bayesian analysis, vol. 6 no. 1 (March, 2011), pp. 145-178, ISSN 1936-0975 [doi]  [abs]
  278. Chen, M; Silva, J; Paisley, J; Wang, C; Dunson, D; Carin, L, Erratum: Compressive sensing on manifolds using a nonparametric mixture of factor analyzers: Algorithm and performance bounds (IEEE Transactions Signal Processing (2011)) 58,12 (6140-6155)), IEEE Transactions on Signal Processing, vol. 59 no. 3 (March, 2011), pp. 1329, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1053-587X [doi]
  279. Pati, D; Reich, BJ; Dunson, DB, Bayesian geostatistical modelling with informative sampling locations., Biometrika, vol. 98 no. 1 (March, 2011), pp. 35-48, ISSN 0006-3444 [doi]  [abs]
  280. Carin, L; Baraniuk, RG; Cevher, V; Dunson, D; Jordan, MI; Sapiro, G; Wakin, MB, Learning Low-Dimensional Signal Models: A Bayesian approach based on incomplete measurements., IEEE signal processing magazine, vol. 28 no. 2 (March, 2011), pp. 39-51, ISSN 1053-5888 [doi]  [abs]
  281. Reich, BJ; Fuentes, M; Dunson, DB, Bayesian Spatial Quantile Regression., Journal of the American Statistical Association, vol. 106 no. 493 (March, 2011), pp. 6-20, ISSN 0162-1459 [repository], [doi]  [abs]
  282. Shi, M; Dunson, DB, Bayesian Variable Selection via Particle Stochastic Search., Statistics & probability letters, vol. 81 no. 2 (February, 2011), pp. 283-291, ISSN 0167-7152 [21278860], [doi]  [abs]
  283. Chung, Y; Dunson, DB, The local Dirichlet process., Annals of the Institute of Statistical Mathematics, vol. 63 no. 1 (February, 2011), pp. 59-80, ISSN 0020-3157 [doi]  [abs]
  284. Ren, L; Du, L; Carin, L; Dunson, DB, Logistic Stick-Breaking Process., Journal of machine learning research : JMLR, vol. 12 no. Jan (January, 2011), pp. 203-239, ISSN 1532-4435  [abs]
  285. Chen, H; Dunson, DB; Carin, L, Topic Modeling with Nonparametric Markov Tree., Proceedings of the ... International Conference on Machine Learning. International Conference on Machine Learning, vol. 2011 (January, 2011), pp. 377-384  [abs]
  286. Zhang, X; Dunson, DB; Carin, L, Tree-Structured Infinite Sparse Factor Model., Proceedings of the ... International Conference on Machine Learning. International Conference on Machine Learning, vol. 2011 (January, 2011), pp. 785-792  [abs]
  287. Chen, M; Zaas, A; Woods, C; Ginsburg, GS; Lucas, J; Dunson, D; Carin, L, Predicting Viral Infection From High-Dimensional Biomarker Trajectories., J Am Stat Assoc, vol. 106 no. 496 (January, 2011), pp. 1259-1279, ISSN 0162-1459 [doi]  [abs]
  288. Ren, L; Wang, Y; Dunson, D; Carin, L, The kernel beta process, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 (January, 2011), ISBN 9781618395993  [abs]
  289. Zhang, XX; Dunson, DB; Carin, L, Hierarchical topic modeling for analysis of time-evolving personal choices, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 (January, 2011), ISBN 9781618395993  [abs]
  290. Armagan, A; Dunson, DB; Clyde, M, Generalized beta mixtures of Gaussians, Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011 (January, 2011), ISBN 9781618395993  [abs]
  291. Armagan, A; Dunson, DB; Clyde, MA, Generalized Beta Mixtures of Gaussians, edited by Shawe-Taylor, J; Zemel, RS; Bartlett, PL, Advances in Neural Information Processing Systems, vol. 24 (2011), pp. 523-531, Neural Information Processing Systems Foundation, Inc, ISBN 9781618395993  [abs]
  292. Zhou, M; Wang, C; Chen, M; Paisley, J; Dunson, D; Carin, L, Nonparametric bayesian matrix completion, 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2010 (December, 2010), pp. 213-216, IEEE [doi]  [abs]
  293. Gordon, GJ; Dunson, D, Preface to the Proceedings of AISTATS 2011, Journal of Machine Learning Research, vol. 9 (December, 2010), pp. 1-2, ISSN 1532-4435
  294. Wang, E; Liu, D; Silva, J; Dunson, D; Carin, L, Joint analysis of time-evolving binary matrices and associated documents, Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010 (December, 2010)  [abs]
  295. Chen, M; Silva, J; Paisley, J; Wang, C; Dunson, D; Carin, L, Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds., IEEE transactions on signal processing : a publication of the IEEE Signal Processing Society, vol. 58 no. 12 (December, 2010), pp. 6140-6155, ISSN 1053-587X [doi]  [abs]
  296. Bhattacharya, A; Dunson, DB, Nonparametric Bayesian density estimation on manifolds with applications to planar shapes., Biometrika, vol. 97 no. 4 (December, 2010), pp. 851-865, ISSN 0006-3444 [22822255], [doi]  [abs]
  297. Chen, B; Chen, M; Paisley, J; Zaas, A; Woods, C; Ginsburg, GS; Hero, A; Lucas, J; Dunson, D; Carin, L, Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies., BMC Bioinformatics, vol. 11 (November, 2010), pp. 552 [21062443], [doi]  [abs]
  298. Blei, D; Carin, L; Dunson, D, Probabilistic Topic Models: A focus on graphical model design and applications to document and image analysis., IEEE signal processing magazine, vol. 27 no. 6 (November, 2010), pp. 55-65, ISSN 1053-5888 [doi]  [abs]
  299. Dunson, DB, MULTIVARIATE KERNEL PARTITION PROCESS MIXTURES., Statistica Sinica, vol. 20 no. 4 (October, 2010), pp. 1395-1422, ISSN 1017-0405  [abs]
  300. Yang, M; Dunson, DB; Baird, D, Semiparametric Bayes hierarchical models with mean and variance constraints., Computational statistics & data analysis, vol. 54 no. 9 (September, 2010), pp. 2172-2186, ISSN 0167-9473 [doi]  [abs]
  301. Cai, B; Dunson, DB; Stanford, JB, Dynamic model for multivariate markers of fecundability., Biometrics, vol. 66 no. 3 (September, 2010), pp. 905-913, ISSN 0006-341X [doi]  [abs]
  302. Stanford, JB; Mikolajczyk, RT; Dunson, DB, Are Chinese people really more fertile?, Fertility and sterility, vol. 94 no. 3 (August, 2010), pp. e58, ISSN 0015-0282 [doi]
  303. Bornkamp, B; Ickstadt, K; Dunson, D, Stochastically ordered multiple regression., Biostatistics (Oxford, England), vol. 11 no. 3 (July, 2010), pp. 419-431, ISSN 1465-4644 [doi]  [abs]
  304. Park, JH; Dunson, DB, Bayesian generalized product partition model, Statistica Sinica, vol. 20 no. 3 (July, 2010), pp. 1203-1226, ISSN 1017-0405 [repository]  [abs]
  305. Maclehose, RF; Dunson, DB, Bayesian semiparametric multiple shrinkage., Biometrics, vol. 66 no. 2 (June, 2010), pp. 455-462, ISSN 0006-341X [doi]  [abs]
  306. Ren, L; Dunson, D; Lindroth, S; Carin, L, Dynamic nonparametric bayesian models for analysis of music, Journal of the American Statistical Association, vol. 105 no. 490 (June, 2010), pp. 458-472, Informa UK Limited, ISSN 0162-1459 [repository], [doi]  [abs]
  307. Rodríguez, A; Dunson, DB; Gelfand, AE, Latent Stick-Breaking Processes., Journal of the American Statistical Association, vol. 105 no. 490 (April, 2010), pp. 647-659, ISSN 0162-1459 [23559690], [doi]  [abs]
  308. Wang, C; Liao, X; Carin, L; Dunson, DB, Classification with Incomplete Data Using Dirichlet Process Priors., Journal of machine learning research : JMLR, vol. 11 (March, 2010), pp. 3269-3311, ISSN 1532-4435  [abs]
  309. Mitra, R; Dunson, D, Two-level stochastic search variable selection in GLMs with missing predictors., The international journal of biostatistics, vol. 6 no. 1 (January, 2010), pp. Article-33, ISSN 1557-4679 [doi]  [abs]
  310. Wang, E; Liu, D; Silva, J; Dunson, D; Carin, L, Joint analysis of time-evolving binary matrices and associated documents, Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010 (January, 2010), ISBN 9781617823800  [abs]
  311. Dunson, DB, Comment on article by Craigmile et al., Bayesian Analysis, vol. 4 no. 1 (December, 2009), pp. 41-44, Institute of Mathematical Statistics, ISSN 1936-0975 [doi]
  312. Chung, Y; Dunson, DB, Nonparametric Bayes Conditional Distribution Modeling With Variable Selection., Journal of the American Statistical Association, vol. 104 no. 488 (December, 2009), pp. 1646-1660, ISSN 0162-1459 [repository], [doi]  [abs]
  313. Ren, L; Dunson, DB; Lindroth, S; Carin, L, Music analysis with a Bayesian dynamic model, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (September, 2009), pp. 1681-1684, IEEE, ISSN 1520-6149 [doi]  [abs]
  314. Wang, C; An, Q; Carin, L; Dunson, DB, Multi-task classification with infinite local experts, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (September, 2009), pp. 1569-1572, IEEE, ISSN 1520-6149 [doi]  [abs]
  315. Scarpa, B; Dunson, DB, Bayesian hierarchical functional data analysis via contaminated informative priors., Biometrics, vol. 65 no. 3 (September, 2009), pp. 772-780, ISSN 0006-341X [doi]  [abs]
  316. Baird, DD; Travlos, G; Wilson, R; Dunson, DB; Hill, MC; D'Aloisio, AA; London, SJ; Schectman, JM, Uterine leiomyomata in relation to insulin-like growth factor-I, insulin, and diabetes., Epidemiology (Cambridge, Mass.), vol. 20 no. 4 (July, 2009), pp. 604-610, ISSN 1044-3983 [doi]  [abs]
  317. Ghosh, J; Dunson, DB, Default Prior Distributions and Efficient Posterior Computation in Bayesian Factor Analysis., Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, vol. 18 no. 2 (June, 2009), pp. 306-320, ISSN 1061-8600 [doi]  [abs]
  318. Dunson, DB, Bayesian nonparametric hierarchical modeling., Biometrical journal. Biometrische Zeitschrift, vol. 51 no. 2 (April, 2009), pp. 273-284 [19358217], [doi]  [abs]
  319. MacLehose, RF; Dunson, DB, Nonparametric Bayes kernel-based priors for functional data analysis, Statistica Sinica, vol. 19 no. 2 (April, 2009), pp. 611-629, ISSN 1017-0405  [abs]
  320. Ji, S; Dunson, D; Carin, L, Multitask compressive sensing, IEEE Transactions on Signal Processing, vol. 57 no. 1 (January, 2009), pp. 92-106, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1053-587X [doi]  [abs]
  321. Rodríguez, A; Dunson, DB; Gelfand, AE, Bayesian Nonparametric Functional Data Analysis Through Density Estimation., Biometrika, vol. 96 no. 1 (January, 2009), pp. 149-162, ISSN 0006-3444 [doi]  [abs]
  322. Du, L; Ren, L; Dunson, DB; Carin, L, A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation., Advances in neural information processing systems, vol. 2009 (January, 2009), pp. 486-494  [abs]
  323. Rodriguez, A; Dunson, DB; Taylor, J, Bayesian hierarchically weighted finite mixture models for samples of distributions., Biostatistics (Oxford, England), vol. 10 no. 1 (January, 2009), pp. 155-171, ISSN 1465-4644 [doi]  [abs]
  324. Bigelow, JL; Dunson, DB, Bayesian semiparametric joint models for functional predictors., Journal of the American Statistical Association, vol. 104 no. 485 (January, 2009), pp. 26-36, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  325. Dunson, DB, Nonparametric Bayes local partition models for random effects., Biometrika, vol. 96 no. 2 (January, 2009), pp. 249-262, ISSN 0006-3444 [doi]  [abs]
  326. Armagan, A; Dunson, DB, Sparse variational analysis of large longitudinal data sets, Statistics & Probability Letters (2009)
  327. Wang, L; Dunson, DB, Semiparametric Bayes multiple testing: Applications to tumor data., Biometrics, vol. 66 no. 2 (2009), pp. 493-501, ISSN 0006-341X [doi]  [abs]
  328. Wang, L; Dunson, DB, Fast Bayesian inference in Dirichlet process mixture models, Journal of Computational & Graphical Statistics, vol. 20 no. 1 (2009), pp. 196-216, Informa UK Limited, ISSN 1061-8600 [doi]  [abs]
  329. Dunson, DB; Peddada, SD, Bayesian nonparametric inference on stochastic ordering., Biometrika, vol. 95 no. 4 (December, 2008), pp. 859-874, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  330. Rodríguez, A; Dunson, DB; Gelfand, AE, The nested Dirichlet process: Rejoinder, Journal of the American Statistical Association, vol. 103 no. 483 (September, 2008), pp. 1153-1154, Informa UK Limited, ISSN 0162-1459 [doi]
  331. Ni, K; Paisley, J; Carin, L; Dunson, D, Multi-task learning for analyzing and sorting large databases of sequential data, IEEE Transactions on Signal Processing, vol. 56 no. 8 II (August, 2008), pp. 3918-3931, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1053-587X [doi]  [abs]
  332. Elliott, L; Henderson, J; Northstone, K; Chiu, GY; Dunson, D; London, SJ, Prospective study of breast-feeding in relation to wheeze, atopy, and bronchial hyperresponsiveness in the Avon Longitudinal Study of Parents and Children (ALSPAC)., The Journal of allergy and clinical immunology, vol. 122 no. 1 (July, 2008), pp. 49-54.e3, ISSN 0091-6749 [doi]  [abs]
  333. Dunson, DB; Herring, AH; Engel, SM, Bayesian selection and clustering of polymorphisms in functionally related genes, Journal of the American Statistical Association, vol. 103 no. 482 (June, 2008), pp. 534-546, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  334. Pennell, ML; Dunson, DB, Nonparametric bayes testing of changes in a response distribution with an ordinal predictor., Biometrics, vol. 64 no. 2 (June, 2008), pp. 413-423, ISSN 0006-341X [doi]  [abs]
  335. Dunson, DB; Park, JH, Kernel stick-breaking processes, Biometrika, vol. 95 no. 2 (June, 2008), pp. 307-323, Oxford University Press (OUP), ISSN 0006-3444 [doi]  [abs]
  336. Dunson, DB, Comment, Journal of the American Statistical Association, vol. 103 no. 481 (March, 2008), pp. 40-41, Informa UK Limited, ISSN 0162-1459 [doi]
  337. Dunson, DB; Xue, Y; Carin, L, The matrix stick-breaking process: Flexible Bayes meta-analysis, Journal of the American Statistical Association, vol. 103 no. 481 (March, 2008), pp. 317-327, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  338. Rodríguez, A; Dunson, DB; Gelfand, AE, The nested dirichlet process, Journal of the American Statistical Association, vol. 103 no. 483 (January, 2008), pp. 1131-1154, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  339. Qi, Y; Liu, D; Dunson, D; Carin, L, Multi-task compressive sensing with dirichlet process priors, Proceedings of the 25th International Conference on Machine Learning (January, 2008), pp. 768-775 [doi]  [abs]
  340. An, Q; Wang, C; Shterev, I; Wang, E; Carin, L; Dunson, DB, Hierarchical kernel stick-breaking process for multi-task image analysis, Proceedings of the 25th International Conference on Machine Learning (January, 2008), pp. 17-24 [doi]  [abs]
  341. Ren, L; Dunson, DB; Carin, L, The dynamic hierarchical Dirichlet process, Proceedings of the 25th International Conference on Machine Learning (January, 2008), pp. 824-831 [doi]  [abs]
  342. Dunson, DB; Herring, A; Siega-Riz, AM, Bayesian Inference on Changes in Response Densities over Predictor Clusters., Journal of the American Statistical Association, vol. 103 no. 484 (January, 2008), pp. 1508-1517, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  343. Rodriguez, A; Dunson, DB; Gelfand, AE, Nonparametric functional data analysis through Bayesian density estimation, Biometrika, vol. 96 (2008), pp. 149-162
  344. Rodriguez, A; Dunson, DB; Gelfand, AE, The nested Dirichlet process (with discussion), Journal of the American Statistical Association (2008)
  345. Yang, M; Dunson, DB, Bayesian semiparametric structural equation models with latent variables, Psychometrika, vol. 75 no. 4 (2008), pp. 675-693, Springer Nature, ISSN 0033-3123 [doi]  [abs]
  346. Palomo, J; Dunson, DB; Bollen, K, Bayesian Structural Equation Modeling (December, 2007), pp. 163-188, Elsevier [doi]  [abs]
  347. Cai, B; Dunson, DB, Bayesian multivariate isotonic regression splines: Applications to carcinogenicity studies, Journal of the American Statistical Association, vol. 102 no. 480 (December, 2007), pp. 1158-1171, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  348. Dunson, DB, Bayesian methods for latent trait modelling of longitudinal data., Statistical methods in medical research, vol. 16 no. 5 (October, 2007), pp. 399-415, ISSN 0962-2802 [doi]  [abs]
  349. Scarpa, B; Dunson, DB; Giacchi, E, Bayesian selection of optimal rules for timing intercourse to conceive by using calendar and mucus., Fertility and sterility, vol. 88 no. 4 (October, 2007), pp. 915-924, ISSN 0015-0282 [doi]  [abs]
  350. Pennell, ML; Dunson, DB, Fitting semiparametric random effects models to large data sets., Biostatistics (Oxford, England), vol. 8 no. 4 (October, 2007), pp. 821-834, ISSN 1465-4644 [doi]  [abs]
  351. Bigelow, JL; Dunson, DB, Bayesian adaptive regression splines for hierarchical data., Biometrics, vol. 63 no. 3 (September, 2007), pp. 724-732, ISSN 0006-341X [17403106], [doi]  [abs]
  352. Xue, Y; Dunson, D; Carin, L, The matrix stick-breaking process for flexible multi-task learning, ACM International Conference Proceeding Series, vol. 227 (August, 2007), pp. 1063-1070, ACM Press [doi]  [abs]
  353. Ni, K; Carin, L; Dunson, D, Multi-task learning for sequential data via iHMMs and the nested Dirichlet process, ACM International Conference Proceeding Series, vol. 227 (August, 2007), pp. 689-696, ACM Press [doi]  [abs]
  354. Stanford, JB; Dunson, DB, Effects of sexual intercourse patterns in time to pregnancy studies., American journal of epidemiology, vol. 165 no. 9 (May, 2007), pp. 1088-1095, ISSN 0002-9262 [doi]  [abs]
  355. Scarpa, B; Dunson, DB, Bayesian methods for searching for optimal rules for timing intercourse to achieve pregnancy., Statistics in medicine, vol. 26 no. 9 (April, 2007), pp. 1920-1936, ISSN 0277-6715 [doi]  [abs]
  356. Dunson, DB; Pillai, N; Park, JH, Bayesian density regression, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 69 no. 2 (April, 2007), pp. 163-183, WILEY, ISSN 1369-7412 [doi]  [abs]
  357. Dunson, DB, Empirical bayes density regression, Statistica Sinica, vol. 17 no. 2 (April, 2007), pp. 481-504, ISSN 1017-0405  [abs]
  358. MacLehose, RF; Dunson, DB; Herring, AH; Hoppin, JA, Bayesian methods for highly correlated exposure data., Epidemiology (Cambridge, Mass.), vol. 18 no. 2 (March, 2007), pp. 199-207, ISSN 1044-3983 [doi]  [abs]
  359. Baird, DD; Dunson, DB; Hill, MC; Cousins, D; Schectman, JM, Association of physical activity with development of uterine leiomyoma., American journal of epidemiology, vol. 165 no. 2 (January, 2007), pp. 157-163, ISSN 0002-9262 [doi]  [abs]
  360. Kinney, S; Dunson, DB, Fixed and random effects selection in linear and logistic models, Biometrics, vol. 63 no. 3 (2007), pp. 690-698, ISSN 0006-341X [17403104], [doi]  [abs]
  361. Pennell, ML; Dunson, DB, Bayesian semiparametric dynamic frailty models for multiple event time data., Biometrics, vol. 62 no. 4 (December, 2006), pp. 1044-1052, ISSN 0006-341X [html], [doi]  [abs]
  362. Stanford, JB; Dunson, DB, Foreword. Expanding Methodologies for Capturing Day-Specific Probabilities of Conception., Paediatric and perinatal epidemiology, vol. 20 Suppl 1 (November, 2006), pp. 1-2, ISSN 0269-5022 [doi]
  363. Scarpa, B; Dunson, DB, Bayesian selection of predictors of conception probabilities across the menstrual cycle., Paediatric and perinatal epidemiology, vol. 20 Suppl 1 no. SUPPL. 1 (November, 2006), pp. 30-37, ISSN 0269-5022 [doi]  [abs]
  364. Dunson, DB, Bayesian dynamic modeling of latent trait distributions., Biostatistics (Oxford, England), vol. 7 no. 4 (October, 2006), pp. 551-568, ISSN 1465-4644 [doi]  [abs]
  365. O'Brien, SM; Kupper, LL; Dunson, DB, Performance of tests of association in misspecified generalized linear models, Journal of Statistical Planning and Inference, vol. 136 no. 9 (September, 2006), pp. 3090-3100, Elsevier BV, ISSN 0378-3758 [doi]  [abs]
  366. Cai, B; Dunson, DB, Bayesian covariance selection in generalized linear mixed models., Biometrics, vol. 62 no. 2 (June, 2006), pp. 446-457, ISSN 0006-341X [html], [doi]  [abs]
  367. Dunson, DB, Special issue of statistical methods in medical research on reproductive studies, Statistical Methods in Medical Research, vol. 15 no. 2 (April, 2006), pp. 91-92, SAGE Publications, ISSN 0962-2802 [doi]
  368. Scarpa, B; Dunson, DB; Colombo, B, Cervical mucus secretions on the day of intercourse: an accurate marker of highly fertile days., European journal of obstetrics, gynecology, and reproductive biology, vol. 125 no. 1 (March, 2006), pp. 72-78 [doi]  [abs]
  369. Baird, DD; Kesner, JS; Dunson, DB, Luteinizing hormone in premenopausal women may stimulate uterine leiomyomata development., Journal of the Society for Gynecologic Investigation, vol. 13 no. 2 (February, 2006), pp. 130-135, ISSN 1071-5576 [doi]  [abs]
  370. Chen, Z; Dunson, DB, The authors replied as follows [2], Biometrics, vol. 62 no. 2 (January, 2006), pp. 623-624, WILEY, ISSN 0006-341X [doi]
  371. Dunson, DB, Bayesian Biostatistics, Handbook of Statistics, vol. 25 (December, 2005), pp. 743-761, Elsevier, ISSN 0169-7161 [doi]  [abs]
  372. Hans, C; Dunson, DB, Bayesian inferences on umbrella orderings., Biometrics, vol. 61 no. 4 (December, 2005), pp. 1018-1026, ISSN 0006-341X [16401275], [doi]  [abs]
  373. Law, DCG; Klebanoff, MA; Brock, JW; Dunson, DB; Longnecker, MP, Maternal serum levels of polychlorinated biphenyls and 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE) and time to pregnancy., American journal of epidemiology, vol. 162 no. 6 (September, 2005), pp. 523-532 [doi]  [abs]
  374. Peddada, SD; Dunson, DB; Tan, X, Estimation of order-restricted means from correlated data, Biometrika, vol. 92 no. 3 (September, 2005), pp. 703-715, Oxford University Press (OUP) [doi]  [abs]
  375. Gueorguieva, RV, Comments about Joint Modeling of Cluster Size and Binary and Continuous Subunit-Specific Outcomes., Biometrics, vol. 61 no. 3 (September, 2005), pp. 862-866, ISSN 0006-341X [doi]  [abs]
  376. Gunn, LH; Dunson, DB, A transformation approach for incorporating monotone or unimodal constraints., Biostatistics (Oxford, England), vol. 6 no. 3 (July, 2005), pp. 434-449, ISSN 1465-4644 [doi]  [abs]
  377. Dunson, DB; Herring, AH, Bayesian model selection and averaging in additive and proportional hazards models., Lifetime data analysis, vol. 11 no. 2 (June, 2005), pp. 213-232 [doi]  [abs]
  378. Dunson, DB, Bayesian semiparametric isotonic regression for count data, Journal of the American Statistical Association, vol. 100 no. 470 (June, 2005), pp. 618-627, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  379. Dunson, DB; Taylor, JA, Approximate Bayesian inference for quantites, Journal of Nonparametric Statistics, vol. 17 no. 3 (April, 2005), pp. 385-400, Informa UK Limited [doi]  [abs]
  380. Dunson, DB; Bigelow, JL; Colombo, B, Reduced fertilization rates in older men when cervical mucus is suboptimal., Obstetrics and gynecology, vol. 105 no. 4 (April, 2005), pp. 788-793, ISSN 0029-7844 [doi]  [abs]
  381. Dunson, DB; Stanford, JB, Bayesian inferences on predictors of conception probabilities., Biometrics, vol. 61 no. 1 (March, 2005), pp. 126-133 [doi]  [abs]
  382. Longnecker, MP; Klebanoff, MA; Dunson, DB; Guo, X; Chen, Z; Zhou, H; Brock, JW, Maternal serum level of the DDT metabolite DDE in relation to fetal loss in previous pregnancies., Environmental research, vol. 97 no. 2 (February, 2005), pp. 127-133, ISSN 0013-9351 [doi]  [abs]
  383. Dunson, DB; Herring, AH, Bayesian latent variable models for mixed discrete outcomes., Biostatistics (Oxford, England), vol. 6 no. 1 (January, 2005), pp. 11-25 [doi]  [abs]
  384. Herring, AH; Dunson, DB; Dole, N, Modeling the effects of a bidirectional latent predictor from multivariate questionnaire data., Biometrics, vol. 60 no. 4 (December, 2004), pp. 926-935, ISSN 0006-341X [doi]  [abs]
  385. Dunson, DB; Holloman, C; Calder, C; Gunn, LH, Bayesian modeling of multiple lesion onset and growth from interval-censored data., Biometrics, vol. 60 no. 3 (September, 2004), pp. 676-683, ISSN 0006-341X [doi]  [abs]
  386. O'Brien, SM; Dunson, DB, Bayesian multivariate logistic regression., Biometrics, vol. 60 no. 3 (September, 2004), pp. 739-746, ISSN 0006-341X [15339297], [doi]  [abs]
  387. Slama, R; Ducot, B; Keiding, N; Bouyer, J, Studying human fertility and environmental exposures., Environmental health perspectives, vol. 112 no. 11 (August, 2004), pp. A604, ISSN 0091-6765 [doi]
  388. Wilcox, AJ; Baird, DD; Dunson, DB; McConnaughey, DR; Kesner, JS; Weinberg, CR, On the frequency of intercourse around ovulation: evidence for biological influences., Human reproduction (Oxford, England), vol. 19 no. 7 (July, 2004), pp. 1539-1543, ISSN 0268-1161 [15190016], [doi]  [abs]
  389. Neelon, B; Dunson, DB, Bayesian isotonic regression and trend analysis., Biometrics, vol. 60 no. 2 (June, 2004), pp. 398-406 [doi]  [abs]
  390. Chen, Z; Dunson, DB, Bayesian estimation of survival functions under stochastic precedence., Lifetime data analysis, vol. 10 no. 2 (June, 2004), pp. 159-173 [doi]  [abs]
  391. Dunson, DB; Chen, Z, Selecting factors predictive of heterogeneity in multivariate event time data., Biometrics, vol. 60 no. 2 (June, 2004), pp. 352-358 [doi]  [abs]
  392. Bigelow, JL; Dunson, DB; Stanford, JB; Ecochard, R; Gnoth, C; Colombo, B, Mucus observations in the fertile window: a better predictor of conception than timing of intercourse., Human reproduction (Oxford, England), vol. 19 no. 4 (April, 2004), pp. 889-892 [doi]  [abs]
  393. Tingen, C; Stanford, JB; Dunson, DB, Methodologic and statistical approaches to studying human fertility and environmental exposure., Environmental health perspectives, vol. 112 no. 1 (January, 2004), pp. 87-93 [doi]  [abs]
  394. Dunson, DB; Baird, DD; Colombo, B, Increased infertility with age in men and women., Obstetrics and gynecology, vol. 103 no. 1 (January, 2004), pp. 51-56 [doi]  [abs]
  395. Trouba, K; Nyska, A; Styblo, M; Dunson, D; Lomnitski, L; Grossman, S; Moser, G; Suttie, A; Patterson, R; Walton, F; Germolec, D, Effect of antioxidants on the papilloma response and liver glutathione modulation mediated by arsenic in tg.ac transgenic mice, Arsenic Exposure and Health Effects V (December, 2003), pp. 283-293, Elsevier [doi]  [abs]
  396. Dunson, DB; Herring, AH, Bayesian inferences in the Cox model for order-restricted hypotheses., Biometrics, vol. 59 no. 4 (December, 2003), pp. 916-923 [doi]  [abs]
  397. Chen, Z; Dunson, DB, Random effects selection in linear mixed models., Biometrics, vol. 59 no. 4 (December, 2003), pp. 762-769 [doi]  [abs]
  398. Dunson, DB; Chen, Z; Harry, J, A Bayesian approach for joint modeling of cluster size and subunit-specific outcomes., Biometrics, vol. 59 no. 3 (September, 2003), pp. 521-530 [doi]  [abs]
  399. Dunson, DB, Dynamic Latent Trait Models for Multidimensional Longitudinal Data, Journal of the American Statistical Association, vol. 98 no. 463 (September, 2003), pp. 555-563, Informa UK Limited [doi]  [abs]
  400. Stanford, JB; Smith, KR; Dunson, DB, Vulvar mucus observations and the probability of pregnancy., Obstetrics and gynecology, vol. 101 no. 6 (June, 2003), pp. 1285-1293 [doi]  [abs]
  401. Dunson, DB; Watson, M; Taylor, JA, Bayesian latent variable models for median regression on multiple outcomes., Biometrics, vol. 59 no. 2 (June, 2003), pp. 296-304 [doi]  [abs]
  402. Dunson, DB; Neelon, B, Bayesian inference on order-constrained parameters in generalized linear models., Biometrics, vol. 59 no. 2 (June, 2003), pp. 286-295 [doi]  [abs]
  403. Dunson, DB, Incorporating heterogeneous intercourse records into time to pregnancy models, Mathematical Population Studies, vol. 10 no. 2 (April, 2003), pp. 127-143, Informa UK Limited, ISSN 0889-8480 [doi]  [abs]
  404. Dunson, DB; Colombo, B, Bayesian modeling of markers of day-specific fertility, Journal of the American Statistical Association, vol. 98 no. 461 (March, 2003), pp. 28-37, Informa UK Limited [doi]  [abs]
  405. Dunson, DB; Chulada, P; Arbes, SJ, Bayesian modeling of time-varying and waning exposure effects., Biometrics, vol. 59 no. 1 (March, 2003), pp. 83-91 [doi]  [abs]
  406. Baird, DD; Dunson, DB, Why is parity protective for uterine fibroids?, Epidemiology (Cambridge, Mass.), vol. 14 no. 2 (March, 2003), pp. 247-250 [doi]  [abs]
  407. Chulada, PC; Arbes, SJ; Dunson, D; Zeldin, DC, Breast-feeding and the prevalence of asthma and wheeze in children: analyses from the Third National Health and Nutrition Examination Survey, 1988-1994., The Journal of allergy and clinical immunology, vol. 111 no. 2 (February, 2003), pp. 328-336 [doi]  [abs]
  408. Baird, DD; Dunson, DB; Hill, MC; Cousins, D; Schectman, JM, High cumulative incidence of uterine leiomyoma in black and white women: ultrasound evidence., American journal of obstetrics and gynecology, vol. 188 no. 1 (January, 2003), pp. 100-107 [doi]  [abs]
  409. Dunson, B; Baird, DD, Bayesian modeling of incidence and progression of disease from cross-sectional data., Biometrics, vol. 58 no. 4 (December, 2002), pp. 813-822 [doi]  [abs]
  410. Zeise, L; Hattis, D; Andersen, M; Bailer, AJ; Bayard, S; Chen, C; Clewell, H; Conolly, R; Crump, K; Dunson, D; Finkel, A; Haber, L; Jarabek, AM; Kodell, R; Krewski, D; Thomas, D; Thorslund, T; Wassell, JT, Improving risk Assessment: Research opportunities in dose response modeling to improve risk assessment, Human and Ecological Risk Assessment, vol. 8 no. 6 (October, 2002), pp. 1421-1444, Informa UK Limited, ISSN 1080-7039 [doi]  [abs]
  411. Mikolajczyk, R, TwoDay Algorithm in predicting fertile time., Human reproduction (Oxford, England), vol. 17 no. 7 (July, 2002), pp. 1925, ISSN 0268-1161 [doi]
  412. Tiano, HF; Loftin, CD; Akunda, J; Lee, CA; Spalding, J; Sessoms, A; Dunson, DB; Rogan, EG; Morham, SG; Smart, RC; Langenbach, R, Deficiency of either cyclooxygenase (COX)-1 or COX-2 alters epidermal differentiation and reduces mouse skin tumorigenesis., Cancer research, vol. 62 no. 12 (June, 2002), pp. 3395-3401  [abs]
  413. Dunson, DB; Colombo, B; Baird, DD, Changes with age in the level and duration of fertility in the menstrual cycle., Human reproduction (Oxford, England), vol. 17 no. 5 (May, 2002), pp. 1399-1403, ISSN 0268-1161 [doi]  [abs]
  414. Dunson, DB; Dinse, GE, Bayesian models for multivariate current status data with informative censoring., Biometrics, vol. 58 no. 1 (March, 2002), pp. 79-88, ISSN 0006-341X [doi]  [abs]
  415. Dunson, DB; Baird, DD, A proportional hazards model for incidence and induced remission of disease., Biometrics, vol. 58 no. 1 (March, 2002), pp. 71-78, ISSN 0006-341X [doi]  [abs]
  416. Dollé, MET; Snyder, WK; Dunson, DB; Vijg, J, Mutational fingerprints of aging., Nucleic acids research, vol. 30 no. 2 (January, 2002), pp. 545-549, ISSN 0305-1048 [doi]  [abs]
  417. Dunson, DB, Bayesian modeling of the level and duration of fertility in the menstrual cycle., Biometrics, vol. 57 no. 4 (December, 2001), pp. 1067-1073 [doi]  [abs]
  418. Dunson, DB; Sinai, I; Colombo, B, The relationship between cervical secretions and the daily probabilities of pregnancy: effectiveness of the TwoDay Algorithm., Human reproduction (Oxford, England), vol. 16 no. 11 (November, 2001), pp. 2278-2282, ISSN 0268-1161 [doi]  [abs]
  419. Wilcox, AJ; Baird, DD; Dunson, D; McChesney, R; Weinberg, CR, Natural limits of pregnancy testing in relation to the expected menstrual period., JAMA, vol. 286 no. 14 (October, 2001), pp. 1759-1761, ISSN 0098-7484 [doi]  [abs]
  420. Nyska, A; Lomnitski, L; Spalding, J; Dunson, DB; Goldsworthy, TL; Ben-Shaul, V; Grossman, S; Bergman, M; Boorman, G, Erratum: Topical and oral administration of the natural water-soluble antioxidant from spinach reduces the multiplicity of papillomas in the Tg.AC mouse model (Toxicology Letters (2001) 122 (33-44) PII: S0378427401003459), Toxicology Letters, vol. 123 no. 2-3 (September, 2001), pp. 237, Elsevier BV, ISSN 0378-4274 [doi]
  421. Robbins, WA; Witt, KL; Haseman, JK; Dunson, DB; Troiani, L; Cohen, MS; Hamilton, CD; Perreault, SD; Libbus, B; Beyler, SA; Raburn, DJ; Tedder, ST; Shelby, MD; Bishop, JB, Antiretroviral therapy effects on genetic and morphologic end points in lymphocytes and sperm of men with human immunodeficiency virus infection., J Infect Dis, vol. 184 no. 2 (July, 2001), pp. 127-135, ISSN 0022-1899 [11424008], [doi]  [abs]
  422. Dunson, DB; Baird, DD, A flexible parametric model for combining current status and age at first diagnosis data., Biometrics, vol. 57 no. 2 (June, 2001), pp. 396-403 [doi]  [abs]
  423. Dunson, DB, Commentary: practical advantages of Bayesian analysis of epidemiologic data., American journal of epidemiology, vol. 153 no. 12 (June, 2001), pp. 1222-1226 [doi]  [abs]
  424. Nyska, A; Lomnitski, L; Spalding, J; Dunson, DB; Goldsworthy, TL; Ben-Shaul, V; Grossman, S; Bergman, M; Boorman, G, Topical and oral administration of the natural water-soluble antioxidant from spinach reduces the multiplicity of papillomas in the Tg.AC mouse model., Toxicology letters, vol. 122 no. 1 (May, 2001), pp. 33-44, ISSN 0378-4274 [doi]  [abs]
  425. Wilcox, AJ; Dunson, DB; Weinberg, CR; Trussell, J; Baird, DD, Likelihood of conception with a single act of intercourse: providing benchmark rates for assessment of post-coital contraceptives., Contraception, vol. 63 no. 4 (April, 2001), pp. 211-215, ISSN 0010-7824 [11376648], [doi]  [abs]
  426. Dunson, DB; Perreault, SD, Factor analytic models of clustered multivariate data with informative censoring., Biometrics, vol. 57 no. 1 (March, 2001), pp. 302-308, ISSN 0006-341X [doi]  [abs]
  427. Dunson, DB, Modeling of changes in tumor burden, Journal of Agricultural, Biological, and Environmental Statistics, vol. 6 no. 1 (March, 2001), pp. 38-48, Springer Nature [doi]  [abs]
  428. Dunson, DB; Weinberg, CR; Baird, DD; Kesner, JS; Wilcox, AJ, Assessing human fertility using several markers of ovulation., Statistics in medicine, vol. 20 no. 6 (March, 2001), pp. 965-978, ISSN 0277-6715 [doi]  [abs]
  429. Dunson, DB; Dinse, GE, Bayesian incidence analysis of animal tumorigenicity data, Journal of the Royal Statistical Society. Series C: Applied Statistics, vol. 50 no. 2 (January, 2001), pp. 125-141, WILEY [doi]  [abs]
  430. Dunson, DB; Zhou, H, A Bayesian Model for Fecundability and Sterility, Journal of the American Statistical Association, vol. 95 no. 452 (December, 2000), pp. 1054-1062, Informa UK Limited, ISSN 0162-1459 [doi]  [abs]
  431. Dunson, DB; Dinse, GE, Distinguishing effects on tumor multiplicity and growth rate in chemoprevention experiments., Biometrics, vol. 56 no. 4 (December, 2000), pp. 1068-1075 [doi]  [abs]
  432. Wilcox, AJ; Dunson, D; Baird, DD, The timing of the "fertile window" in the menstrual cycle: day specific estimates from a prospective study., BMJ (Clinical research ed.), vol. 321 no. 7271 (November, 2000), pp. 1259-1262, ISSN 0959-8146 [doi]  [abs]
  433. Dunson, DB; Tindall, KR, Bayesian analysis of mutational spectra., Genetics, vol. 156 no. 3 (November, 2000), pp. 1411-1418 [doi]  [abs]
  434. Dunson, DB, Assessing overall risk in reproductive experiments., Risk analysis : an official publication of the Society for Risk Analysis, vol. 20 no. 4 (August, 2000), pp. 429-437 [doi]  [abs]
  435. Dunson, DB; Haseman, JK; van Birgelen, AP; Stasiewicz, S; Tennant, RW, Statistical analysis of skin tumor data from Tg.AC mouse bioassays., Toxicological sciences : an official journal of the Society of Toxicology, vol. 55 no. 2 (June, 2000), pp. 293-302 [doi]  [abs]
  436. Dunson, DB; Weinberg, CR, Modeling human fertility in the presence of measurement error., Biometrics, vol. 56 no. 1 (March, 2000), pp. 288-292, ISSN 0006-341X [doi]  [abs]
  437. Weinberg, CR; Dunson, DB, Some Issues in Assessing Human Fertility, in Statistics in the 21st Century, Journal of the American Statistical Association, vol. 95 no. 449 (March, 2000), pp. 300-303, Informa UK Limited, ISSN 0162-1459, ISBN 9781420035391 [doi]  [abs]
  438. Dunson, DB, Models for papilloma multiplicity and regression: Applications to transgenic mouse studies, Journal of the Royal Statistical Society. Series C: Applied Statistics, vol. 49 no. 1 (January, 2000), pp. 19-30, WILEY [doi]  [abs]
  439. Dunson, DB, Bayesian latent variable models for clustered mixed outcomes, Journal of the Royal Statistical Society. Series B: Statistical Methodology, vol. 62 no. 2 (January, 2000), pp. 355-366, WILEY [doi]  [abs]
  440. Dunson, DB; Weinberg, CR, Accounting for unreported and missing intercourse in human fertility studies, Statistics in Medicine, vol. 19 no. 5 (2000), pp. 665-679, ISSN 0277-6715 [doi]  [abs]
  441. Dunson, DB; Haseman, JK, Modeling tumor onset and multiplicity using transition models with latent variables., Biometrics, vol. 55 no. 3 (September, 1999), pp. 965-970, ISSN 0006-341X [doi]  [abs]
  442. Dunson, WA; Dunson, DB, Factors influencing growth and survival of the killifish, Rivulus marmoratus, held inside enclosures in mangrove swamps, Copeia, vol. 1999 no. 3 (August, 1999), pp. 661-668, JSTOR [doi]  [abs]
  443. Dunson, DB; Baird, DD; Wilcox, AJ; Weinberg, CR, Day-specific probabilities of clinical pregnancy based on two studies with imperfect measures of ovulation., Human reproduction (Oxford, England), vol. 14 no. 7 (July, 1999), pp. 1835-1839, ISSN 0268-1161 [doi]  [abs]
  444. Dunson, DB; Weinberg, CR; Perreault, SD; Chapin, RE, Summarizing the motion of self-propelled cells: applications to sperm motility., Biometrics, vol. 55 no. 2 (June, 1999), pp. 537-543, ISSN 0006-341X [doi]  [abs]
  445. Dunson, DB, Dose-dependent number of implants and implications in developmental toxicity., Biometrics, vol. 54 no. 2 (June, 1998), pp. 558-569, ISSN 0006-341X [doi]  [abs]
  446. Dunson, WA; Paradise, CJ; Dunson, DB, Inhibitory effect of low salinity on growth and reproduction of the estuarine sheepshead minnow, Cyprinodon variegatus, Copeia, vol. 1998 no. 1 (February, 1998), pp. 235-239, JSTOR [doi]

Papers Submitted

  1. R. Mitra and D.B. Dunson, Two level stochastic search variable selection in GLMs with missing predictors (2008)
  2. B. Cai and D.B. Dunson, Variable selection in nonparametric random effects models, submitted (2007)
  3. L.Wang and D.B. Dunson, Bayesian isotonic density regression (2007)

Chapters

  1. Dunson, DB, Nonparametric Bayes, in Past, Present, and Future of Statistical Science (January, 2014), pp. 281-291, ISBN 9781482204964  [abs]
  2. Dunson, DB; Bhattacharya, A; Griffin, JE, Nonparametric Bayes Regression and Classification Through Mixtures of Product Kernels, in Bayesian Statistics 9, vol. 9780199694587 (January, 2012), pp. 145-164, Oxford University Press, ISBN 9780199694587 [doi]  [abs]
  3. Weinberg, CR; Dunson, DB, Some issues in assessing human fertility, in Statistics in the 21st Century (January, 2001), pp. 42-49, ISBN 9781584882725  [abs]

 

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