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Mathematics : Publications since January 2016

List all publications in the database.    :chronological  alphabetical  by author  bibtex listing:

  1. Tralie, CJ; Smith, A; Borggren, N; Hineman, J; Bendich, P; Zulch, P; Harer, J, Geometric Cross-Modal Comparison of Heterogeneous Sensor Data, Proceedings of the 39th IEEE Aerospace Conference (March, 2018)  [abs]
  2. Kiselev, A; Tan, C, Finite time blow up in the hyperbolic Boussinesq system, Advances in Mathematics, vol. 325 (February, 2018), pp. 34-55 [doi]  [abs]
  3. Arlotto, A; Wei, Y; Xie, X, An adaptive O(log n)-optimal policy for the online selection of a monotone subsequence from a random sample, Random Structures and Algorithms, vol. 52 no. 1 (January, 2018), pp. 41-53, Wiley [doi]  [abs]
  4. Kowalski, M; Meynard, A; Wu, H-T, Convex Optimization approach to signals with fast varying instantaneous frequency, Applied and Computational Harmonic Analysis, vol. 44 no. 1 (January, 2018), pp. 89-122 [doi]
  5. Arlotto, A; Frazelle, AE; Wei, Y, Strategic open routing in service networks, Management Science (2018), INFORMS
  6. Arlotto, A; Steele, JM, A central limit theorem for costs in Bulinskaya’s inventory management problem when deliveries face delays, Methodology and Computing in Applied Probability (2018) [doi]
  7. Gleeson, JP; Durrett, R, Temporal profiles of avalanches on networks, Nature Communications, vol. 8 no. 1 (December, 2017) [doi]
  8. Chao, Y-S; Wu, H-T; Scutari, M; Chen, T-S; Wu, C-J; Durand, M; Boivin, A, A network perspective on patient experiences and health status: the Medical Expenditure Panel Survey 2004 to 2011, BMC Health Services Research, vol. 17 no. 1 (December, 2017) [doi]
  9. Li, Y; Ying, L, Distributed-memory hierarchical interpolative factorization, Research in the Mathematical Sciences, vol. 4 no. 1 (December, 2017) [doi]
  10. Motta, FC, Topological Data Analysis: Developments and Applications, in Advances in Nonlinear Geosciences, edited by Tsonis, A (November, 2017), pp. 369-391, Springer, ISBN 3319588958  [abs]
  11. Reed, M; Best, J; Golubitsky, M; Stewart, I; Nijhout, HF, Analysis of Homeostatic Mechanisms in Biochemical Networks., Bulletin of Mathematical Biology, vol. 79 no. 11 (November, 2017), pp. 2534-2557 [doi]  [abs]
  12. Edwards, A; Layton, AT, Cell Volume Regulation in the Proximal Tubule of Rat Kidney : Proximal Tubule Cell Volume Regulation., Bulletin of Mathematical Biology, vol. 79 no. 11 (November, 2017), pp. 2512-2533 [doi]  [abs]
  13. Little, AV; Maggioni, M; Rosasco, L, Multiscale geometric methods for data sets I: Multiscale SVD, noise and curvature, Applied and Computational Harmonic Analysis, vol. 43 no. 3 (November, 2017), pp. 504-567 [doi]
  14. Cao, Y; Feng, Y; Ryser, MD; Zhu, K; Herschlag, G; Cao, C; Marusak, K; Zauscher, S; You, L, Programmable assembly of pressure sensors using pattern-forming bacteria., Nature Biotechnology, vol. 35 no. 11 (November, 2017), pp. 1087-1093 [doi]  [abs]
  15. Carneiro, E; Madrid, J; Pierce, LB, Endpoint Sobolev and BV continuity for maximal operators, Journal of Functional Analysis, vol. 273 no. 10 (November, 2017), pp. 3262-3294 [doi]
  16. Heath-Brown, DR; Pierce, LB, Averages and moments associated to class numbers of imaginary quadratic fields, Compositio Mathematica, vol. 153 no. 11 (November, 2017), pp. 2287-2309 [doi]
  17. Randles, A; Frakes, DH; Leopold, JA, Computational Fluid Dynamics and Additive Manufacturing to Diagnose and Treat Cardiovascular Disease., Trends in Biotechnology, vol. 35 no. 11 (November, 2017), pp. 1049-1061 [doi]  [abs]
  18. Choi, K; Hou, TY; Kiselev, A; Luo, G; Sverak, V; Yao, Y, On the Finite-Time Blowup of a One-Dimensional Model for the Three-Dimensional Axisymmetric Euler Equations, Communications on Pure & Applied Mathematics, vol. 70 no. 11 (November, 2017), pp. 2218-2243 [doi]
  19. Arlotto, A; Gurvich, I, Uniformly bounded regret in the multi-secretary problem (October, 2017)  [abs]
  20. Gao, T; Yapuncich, GS; Daubechies, I; Mukherjee, S; Boyer, DM, Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation., The Anatomical Record : Advances in Integrative Anatomy and Evolutionary Biology (October, 2017) [doi]  [abs]
  21. Gao, T; Yapuncich, GS; Daubechies, I; Mukherjee, S; Boyer, DM, Development and Assessment of Fully Automated and Globally Transitive Geometric Morphometric Methods, With Application to a Biological Comparative Dataset With High Interspecific Variation., The Anatomical Record : Advances in Integrative Anatomy and Evolutionary Biology (October, 2017) [doi]  [abs]
  22. Agarwal, PK; Har-Peled, S; Suri, S; Yıldız, H; Zhang, W, Convex Hulls Under Uncertainty, Algorithmica, vol. 79 no. 2 (October, 2017), pp. 340-367 [doi]
  23. Kiehart, DP; Crawford, JM; Aristotelous, A; Venakides, S; Edwards, GS, Cell Sheet Morphogenesis: Dorsal Closure in Drosophila melanogaster as a Model System., Annual Review of Cell and Developmental Biology, vol. 33 (October, 2017), pp. 169-202 [doi]  [abs]
  24. 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 et al., Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma., Cell, vol. 171 no. 2 (October, 2017), pp. 481-494.e15 [doi]  [abs]
  25. Li, L; Liu, J-G; Lu, J, Fractional Stochastic Differential Equations Satisfying Fluctuation-Dissipation Theorem, Journal of Statistical Physics, vol. 169 no. 2 (October, 2017), pp. 316-339 [doi]
  26. Li, L; Liu, J-G; Lu, J, Fractional Stochastic Differential Equations Satisfying Fluctuation-Dissipation Theorem, Journal of Statistical Physics, vol. 169 no. 2 (October, 2017), pp. 316-339 [doi]  [abs]
  27. Cho, C-Y; Motta, FC; Kelliher, CM; Deckard, A; Haase, SB, Reconciling conflicting models for global control of cell-cycle transcription., Cell Cycle, vol. 16 no. 20 (October, 2017), pp. 1965-1978 [doi]  [abs]
  28. Li, L; Liu, J-G; Lu, J, Fractional Stochastic Differential Equations Satisfying Fluctuation-Dissipation Theorem, Journal of Statistical Physics, vol. 169 no. 2 (October, 2017), pp. 316-339 [doi]
  29. Wu, H-K; Ko, Y-S; Lin, Y-S; Wu, H-T; Tsai, T-H; Chang, H-H, Corrigendum to “The correlation between pulse diagnosis and constitution identification in traditional Chinese medicine” [Complementary Ther. Med. 30 (2017) 107–112], Complementary Therapies in Medicine (October, 2017) [doi]
  30. Tralie, CJ, Early MFCC And HPCP Fusion for Robust Cover Song Identification, 18th International Society for Music Information Retrieval (ISMIR) (October, 2017)  [abs]
  31. Frasch, MG; Boylan, GB; Wu, H-T; Devane, D, Commentary: Computerised interpretation of fetal heart rate during labour (INFANT): a randomised controlled trial, Frontiers in Physiology, vol. 8 (September, 2017) [doi]
  32. Pierce, LB; Turnage-Butterbaugh, CL; Wood, MM, An effective Chebotarev density theorem for families of number fields, with an application to $\ell$-torsion in class groups, (submitted) (September, 2017)  [abs]
  33. Pierce, LB; Turnage-Butterbaugh, CL; Wood, MM, An effective Chebotarev density theorem for families of number fields, with an application to $\ell$-torsion in class groups, (submitted) (September, 2017)  [abs]
  34. Cicone, A; Wu, H-T, How Nonlinear-Type Time-Frequency Analysis Can Help in Sensing Instantaneous Heart Rate and Instantaneous Respiratory Rate from Photoplethysmography in a Reliable Way, Frontiers in Physiology, vol. 8 (September, 2017) [doi]
  35. Robles, C, Characterization of Calabi–Yau variations of Hodge structure over tube domains by characteristic forms, Mathematische Annalen (September, 2017), pp. 1-25 [doi]  [abs]
  36. Zhang, L; Sun, L; Guan, Z; Lee, S; Li, Y; Deng, HD; Li, Y; Ahlborg, NL; Boloor, M; Melosh, NA; Chueh, WC, Quantifying and Elucidating Thermally Enhanced Minority Carrier Diffusion Length Using Radius-Controlled Rutile Nanowires, Nano Letters, vol. 17 no. 9 (September, 2017), pp. 5264-5272 [doi]
  37. Pisharady, PK; Sotiropoulos, SN; Sapiro, G; Lenglet, C, A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI., Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, vol. 10433 (September, 2017), pp. 602-610, ISBN 9783319661810 [doi]  [abs]
  38. Herschlag, G; Ravier, R; Mattingly, JC, Evaluating Partisan Gerrymandering in Wisconsin (September, 2017)  [abs]
  39. Agarwal, PK; Rubin, N; Sharir, M, Approximate nearest neighbor search amid higher-dimensional flats, LIPIcs, vol. 87 (September, 2017), ISBN 9783959770491 [doi]  [abs]
  40. Li, C; Srivastava, S; Dunson, DB, Simple, scalable and accurate posterior interval estimation, Biometrika, vol. 104 no. 3 (September, 2017), pp. 665-680 [doi]
  41. 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]
  42. Srivastava, S; Engelhardt, BE; Dunson, DB, Expandable factor analysis, Biometrika, vol. 104 no. 3 (September, 2017), pp. 649-663 [doi]
  43. Burt, T; Noveck, RJ; MacLeod, DB; Layton, AT; Rowland, M; Lappin, G, Intra-Target Microdosing (ITM): A Novel Drug Development Approach Aimed at Enabling Safer and Earlier Translation of Biological Insights Into Human Testing., Clinical and Translational Science, vol. 10 no. 5 (September, 2017), pp. 337-350 [doi]
  44. Sgouralis, I; Evans, RG; Layton, AT, Renal medullary and urinary oxygen tension during cardiopulmonary bypass in the rat., Mathematical Medicine and Biology: A Journal of the IMA, vol. 34 no. 3 (September, 2017), pp. 313-333 [doi]  [abs]
  45. Peco, C; Chen, W; Liu, Y; Bandi, MM; Dolbow, JE; Fried, E, Influence of surface tension in the surfactant-driven fracture of closely-packed particulate monolayers., Soft Matter, vol. 13 no. 35 (September, 2017), pp. 5832-5841 [doi]  [abs]
  46. Sokolić, J; Giryes, R; Sapiro, G; Rodrigues, MRD, Generalization error of deep neural networks: Role of classification margin and data structure, 2017 12th International Conference on Sampling Theory and Applications, SampTA 2017 (September, 2017), pp. 147-151, ISBN 9781538615652 [doi]  [abs]
  47. Yu, VW-Z; Corsetti, F; García, A; Huhn, WP; Jacquelin, M; Jia, W; Lange, B; Lin, L; Lu, J; Mi, W; Seifitokaldani, A; Vázquez-Mayagoitia, Á; Yang, C; Yang, H; Blum, V, ELSI: A unified software interface for Kohn–Sham electronic structure solvers, Computer Physics Communications (September, 2017) [doi]
  48. Lu, J; Thicke, K, Cubic scaling algorithms for RPA correlation using interpolative separable density fitting, Journal of Computational Physics (September, 2017) [doi]
  49. Charbonneau, P; Li, YC; Pfister, HD; Yaida, S, Cycle-expansion method for the Lyapunov exponent, susceptibility, and higher moments, Physical review. E, vol. 96 no. 3 (September, 2017) [doi]
  50. Hoffman, C; Johnson, T; Junge, M, Recurrence and transience for the frog model on trees, Annals of Probability, vol. 45 no. 5 (September, 2017), pp. 2826-2854 [doi]
  51. Lu, J; Steinerberger, S, A variation on the Donsker-Varadhan inequality for the principal eigenvalue., Proceedings of the Royal Society of London: Mathematical, Physical and Engineering Sciences, vol. 473 no. 2204 (August, 2017), pp. 20160877 [doi]  [abs]
  52. Lin, T-Y; Fang, Y-F; Huang, S-H; Wang, T-Y; Kuo, C-H; Wu, H-T; Kuo, H-P; Lo, Y-L, Capnography monitoring the hypoventilation during the induction of bronchoscopic sedation: A randomized controlled trial., Scientific Reports, vol. 7 no. 1 (August, 2017), pp. 8685 [doi]  [abs]
  53. Sokolic, J; Giryes, R; Sapiro, G; Rodrigues, MRD, Robust Large Margin Deep Neural Networks, IEEE Transactions on Signal Processing, vol. 65 no. 16 (August, 2017), pp. 4265-4280 [doi]
  54. Tomasetti, C; Durrett, R; Kimmel, M; Lambert, A; Parmigiani, G; Zauber, A; Vogelstein, B, Role of stem-cell divisions in cancer risk, Nature, vol. 548 no. 7666 (August, 2017), pp. E13-E14 [doi]
  55. Agarwal, PK; Kumar, N; Sintos, S; Suri, S, Efficient algorithms for k-regret minimizing sets, LIPIcs, vol. 75 (August, 2017), ISBN 9783959770361 [doi]  [abs]
  56. Bakhtin, Y; Hurth, T; Lawley, SD; Mattingly, JC, Smooth invariant densities for random switching on the torus (August, 2017)  [abs]
  57. Guhaniyogi, R; Qamar, S; Dunson, DB, Bayesian tensor regression, Journal of machine learning research : JMLR, vol. 18 (August, 2017), pp. 1-31  [abs]
  58. Chen, Y; Sullivan, JC; Edwards, A; Layton, AT, Sex-specific computational models of the spontaneously hypertensive rat kidneys: factors affecting nitric oxide bioavailability., American Journal of Physiology: Renal Physiology, vol. 313 no. 2 (August, 2017), pp. F174-F183 [doi]  [abs]
  59. Layton, AT; Edwards, A; Vallon, V, Adaptive changes in GFR, tubular morphology, and transport in subtotal nephrectomized kidneys: modeling and analysis., American Journal of Physiology: Renal Physiology, vol. 313 no. 2 (August, 2017), pp. F199-F209 [doi]  [abs]
  60. Gerber, S; Maggioni, M, Multiscale strategies for computing optimal transport, Journal of machine learning research : JMLR, vol. 18 (August, 2017), pp. 1-32  [abs]
  61. Orizaga, S; Riahi, DN, Triad resonant wave interactions in electrically charged jets, Applied Mathematics and Mechanics, vol. 38 no. 8 (August, 2017), pp. 1127-1148 [doi]
  62. Johndrow, JE; Mattingly, JC, Coupling and Decoupling to bound an approximating Markov Chain (July, 2017)  [abs]
  63. Aigerman, N; Kovalsky, SZ; Lipman, Y, Spherical orbifold tutte embeddings, ACM Transactions on Graphics, vol. 36 no. 4 (July, 2017), pp. 1-13 [doi]
  64. Shtengel, A; Poranne, R; Sorkine-Hornung, O; Kovalsky, SZ; Lipman, Y, Geometric optimization via composite majorization, ACM Transactions on Graphics, vol. 36 no. 4 (July, 2017), pp. 1-11 [doi]
  65. Pierce, LB, The Vinogradov Mean Value Theorem [after Wooley, and Bourgain, Demeter and Guth], Asterisque (July, 2017), Centre National de la Recherche Scientifique  [abs]
  66. 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 (July, 2017), pp. 1261-1273 [doi]
  67. Gao, Y; Ji, H; Liu, J-G; Witelski, TP, Global existence of solutions to a tear film model with locally elevated evaporation rates, Physica D: Nonlinear Phenomena, vol. 350 (July, 2017), pp. 13-25 [doi]
  68. Chen, Y; Fry, BC; Layton, AT, Modeling glucose metabolism and lactate production in the kidney., Mathematical Biosciences, vol. 289 (July, 2017), pp. 116-129 [doi]  [abs]
  69. Liu, J-G; Ma, Z; Zhou, Z, Explicit and Implicit TVD Schemes for Conservation Laws with Caputo Derivatives, Journal of Scientific Computing, vol. 72 no. 1 (July, 2017), pp. 291-313 [doi]
  70. Gao, Y; Ji, H; Liu, J-G; Witelski, TP, Global existence of solutions to a tear film model with locally elevated evaporation rates, Physica D: Nonlinear Phenomena, vol. 350 (July, 2017), pp. 13-25 [doi]
  71. Lu, J; Yang, H, A cubic scaling algorithm for excited states calculations in particle–particle random phase approximation, Journal of Computational Physics, vol. 340 (July, 2017), pp. 297-308 [doi]
  72. Liu, J-G; Ma, Z; Zhou, Z, Explicit and Implicit TVD Schemes for Conservation Laws with Caputo Derivatives, Journal of Scientific Computing, vol. 72 no. 1 (July, 2017), pp. 291-313 [doi]  [abs]
  73. Burris, CS; Motta, FC; Shipman, PD, An Unoriented Variation on de Bruijn Sequences, Graphs and Combinatorics, vol. 33 no. 4 (July, 2017), pp. 845-858 [doi]
  74. Kudekar, S; Kumar, S; Mondelli, M; Pfister, HD; Sasoglu, E; Urbanke, RL, Reed–Muller Codes Achieve Capacity on Erasure Channels, IEEE Transactions on Information Theory, vol. 63 no. 7 (July, 2017), pp. 4298-4316 [doi]
  75. Hager, C; Pfister, HD; Graell i Amat, A; Brannstrom, F, Density Evolution for Deterministic Generalized Product Codes on the Binary Erasure Channel at High Rates, IEEE Transactions on Information Theory (July, 2017) [doi]
  76. Kerr, M; Robles, C, Variations of Hodge structure and orbits in flag varieties, Advances in Mathematics, vol. 315 (July, 2017), pp. 27-87 [doi]  [abs]
  77. Lu, J; Yang, H, A cubic scaling algorithm for excited states calculations in particle–particle random phase approximation, Journal of Computational Physics, vol. 340 (July, 2017), pp. 297-308 [doi]
  78. Kiselev, A; Yao, Y; Zlatoš, A, Local Regularity for the Modified SQG Patch Equation, Communications on Pure & Applied Mathematics, vol. 70 no. 7 (July, 2017), pp. 1253-1315 [doi]
  79. Malik, J; Reed, N; Wang, C-L; Wu, H-T, Single-lead f-wave extraction using diffusion geometry, Physiological Measurement, vol. 38 no. 7 (July, 2017), pp. 1310-1334 [doi]
  80. Georgiou, A; Bello-Rivas, J; Gear, C; Wu, H-T; Chiavazzo, E; Kevrekidis, I, An Exploration Algorithm for Stochastic Simulators Driven by Energy Gradients, Entropy (Basel, Switzerland), vol. 19 no. 7 (July, 2017), pp. 294-294 [doi]
  81. Glatt-Holtz, NE; Herzog, DP; Mattingly, JC, Scaling and Saturation in Infinite-Dimensional Control Problems with Applications to Stochastic Partial Differential Equations (June, 2017)  [abs]
  82. Pisharady, PK; Sotiropoulos, SN; Duarte-Carvajalino, JM; Sapiro, G; Lenglet, C, Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning., NeuroImage (June, 2017) [doi]  [abs]
  83. Gounley, J; Vardhan, M; Randles, A, A computational framework to assess the influence of changes in vascular geometry on blood flow, PASC 2017 - Proceedings of the Platform for Advanced Scientific Computing Conference (June, 2017), ISBN 9781450350624 [doi]  [abs]
  84. Nanda, M; Durrett, R, Spatial evolutionary games with weak selection, Proceedings of the National Academy of Sciences of USA, vol. 114 no. 23 (June, 2017), pp. 6046-6051 [doi]
  85. Agarwal, PK; Fox, K; Panigrahi, D; Varadarajan, KR; Xiao, A, Faster algorithms for the geometric transportation problem, LIPIcs, vol. 77 (June, 2017), pp. 71-716, ISBN 9783959770385 [doi]  [abs]
  86. Bryant, RL; Huang, L; Mo, X, On Finsler surfaces of constant flag curvature with a Killing field, Journal of Geometry and Physics, vol. 116 (June, 2017), pp. 345-357 [doi]
  87. 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 and Behavior, vol. 7 no. 6 (June, 2017), pp. e00710 [doi]  [abs]
  88. Zhu, B; Dunson, DB, Bayesian Functional Data Modeling for Heterogeneous Volatility, Bayesian Analysis, vol. 12 no. 2 (June, 2017), pp. 335-350 [doi]
  89. Wang, L; Durante, D; Jung, RE; Dunson, DB, Bayesian network-response regression., Bioinformatics, vol. 33 no. 12 (June, 2017), pp. 1859-1866 [doi]  [abs]
  90. Gao, Y; Liu, J-G; Lu, J, Continuum Limit of a Mesoscopic Model with Elasticity of Step Motion on Vicinal Surfaces, Journal of Nonlinear Science, vol. 27 no. 3 (June, 2017), pp. 873-926 [doi]
  91. Bessonov, M; Durrett, R, Phase transitions for a planar quadratic contact process, Advances in Applied Mathematics, vol. 87 (June, 2017), pp. 82-107 [doi]
  92. Wang, L; Chen, M; Rodrigues, M; Wilcox, D; Calderbank, R; Carin, L, Information-Theoretic Compressive Measurement Design., IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39 no. 6 (June, 2017), pp. 1150-1164 [doi]  [abs]
  93. Gao, Y; Liu, J-G; Lu, J, Continuum Limit of a Mesoscopic Model with Elasticity of Step Motion on Vicinal Surfaces, Journal of Nonlinear Science, vol. 27 no. 3 (June, 2017), pp. 873-926 [doi]
  94. Li, C; Lu, J; Yang, W, On extending Kohn-Sham density functionals to systems with fractional number of electrons., Journal of Chemical Physics, vol. 146 no. 21 (June, 2017), pp. 214109 [doi]  [abs]
  95. Kerr, M; Robles, C, Classification of smooth horizontal Schubert varieties, European Journal of Mathematics, vol. 3 no. 2 (June, 2017), pp. 289-310 [doi]
  96. Sheu, Y-L; Hsu, L-Y; Chou, P-T; Wu, H-T, Entropy-based time-varying window width selection for nonlinear-type time–frequency analysis, International Journal of Data Science and Analytics, vol. 3 no. 4 (June, 2017), pp. 231-245 [doi]
  97. 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 of the Royal Society of London: Biological Sciences, vol. 284 no. 1855 (May, 2017), pp. 20170768-20170768 [doi]
  98. Li, R; Frasch, MG; Wu, H-T, Efficient Fetal-Maternal ECG Signal Separation from Two Channel Maternal Abdominal ECG via Diffusion-Based Channel Selection, Frontiers in Physiology, vol. 8 (May, 2017) [doi]
  99. Hadani, R; Rakib, S; Tsatsanis, M; Monk, A; Goldsmith, AJ; Molisch, AF; Calderbank, R, Orthogonal time frequency space modulation, IEEE Wireless Communications and Networking Conference (May, 2017), ISBN 9781509041831 [doi]  [abs]
  100. 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]
  101. 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., The Journal of Experimental Medicine, vol. 214 no. 5 (May, 2017), pp. 1371-1386 [doi]  [abs]
  102. Bongini, M; Fornasier, M; Hansen, M; Maggioni, M, Inferring interaction rules from observations of evolutive systems I: The variational approach, Mathematical Models & Methods in Applied Sciences, vol. 27 no. 05 (May, 2017), pp. 909-951 [doi]
  103. Lu, J; Thicke, K, Orbital minimization method with ℓ 1 regularization, Journal of Computational Physics, vol. 336 (May, 2017), pp. 87-103 [doi]
  104. Dabagh, M; Jalali, P; Butler, PJ; Randles, A; Tarbell, JM, Mechanotransmission in endothelial cells subjected to oscillatory and multi-directional shear flow., Journal of the Royal Society Interface, vol. 14 no. 130 (May, 2017) [doi]  [abs]
  105. Simhal, AK; Aguerrebere, C; Collman, F; Vogelstein, JT; Micheva, KD; Weinberg, RJ; Smith, SJ; Sapiro, G, Probabilistic fluorescence-based synapse detection., PLoS computational biology, vol. 13 no. 4 (April, 2017), pp. e1005493 [doi]  [abs]
  106. Jockers, H; Katz, S; Morrison, DR; Plesser, MR, SU(N) Transitions in M-Theory on Calabi–Yau Fourfolds and Background Fluxes, Communications in Mathematical Physics, vol. 351 no. 2 (April, 2017), pp. 837-871 [doi]
  107. 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 [doi]
  108. 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 et al., The Genetic Basis of Hepatosplenic T-cell Lymphoma., Cancer Discovery, vol. 7 no. 4 (April, 2017), pp. 369-379 [doi]  [abs]
  109. 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 [doi]
  110. Layton, AT, A new microscope for the kidney: mathematics., American Journal of Physiology: Renal Physiology, vol. 312 no. 4 (April, 2017), pp. F671-F672 [doi]
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