Mathematics Faculty: Publications since January 2017
List all publications in the database. :chronological alphabetical combined bibtex listing:
Agarwal, Pankaj K.
 Agarwal, PK; Kyle, FOX; Salzman, O, An efficient algorithm for computing highquality paths amid polygonal obstacles,
Acm Transactions on Algorithms, vol. 14 no. 4
(August, 2018) [doi] [abs]
 Agarwal, PK; Kaplan, H; Sharir, M, Union of hypercubes and 3D minkowski sums with random sizes,
Leibniz International Proceedings in Informatics, Lipics, vol. 107
(July, 2018), ISBN 9783959770767 [doi] [abs]
 Agarwal, PK; Kumar, N; Sintos, S; Suri, S, Rangemax queries on uncertain data,
Journal of Computer and System Sciences, vol. 94
(June, 2018),
pp. 118134 [doi] [abs]
 Agarwal, PK; Arge, L; Staals, F, Improved dynamic geodesic nearest neighbor searching in a simple polygon,
Leibniz International Proceedings in Informatics, Lipics, vol. 99
(June, 2018),
pp. 41414 [doi] [abs]
 Agarwal, PK; Kumar, N; Sintos, S; Suri, S, Computing shortest paths in the plane with removable obstacles,
Leibniz International Proceedings in Informatics, Lipics, vol. 101
(June, 2018),
pp. 51515, ISBN 9783959770682 [doi] [abs]
 Agarwal, PK; Fox, K; Munagala, K; Nath, A; Pan, J; Taylor, E, Subtrajectory clustering: Models and algorithms,
Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems
(May, 2018),
pp. 7587, ISBN 9781450347068 [doi] [abs]
 Agarwal, PK; Fox, K; Nath, A; Sidiropoulos, A; Wang, Y, Computing the GromovHausdorff Distance for Metric Trees,
Acm Transactions on Algorithms, vol. 14 no. 2
(April, 2018),
pp. 120 [doi]
 Agarwal, PK; Fox, K; Nath, A, Maintaining reeb graphs of triangulated 2manifolds,
Leibniz International Proceedings in Informatics, Lipics, vol. 93
(January, 2018), ISBN 9783959770552 [doi] [abs]
 Rav, M; Lowe, A; Agarwal, PK, Flood Risk Analysis on Terrains,
GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, vol. 2017November
(November, 2017), ISBN 9781450354905 [doi] [abs]
 Agarwal, PK; HarPeled, S; Suri, S; Yıldız, H; Zhang, W, Convex Hulls Under Uncertainty,
Algorithmica, vol. 79 no. 2
(October, 2017),
pp. 340367 [doi]
 Agarwal, PK; Rubin, N; Sharir, M, Approximate nearest neighbor search amid higherdimensional flats,
Leibniz International Proceedings in Informatics, Lipics, vol. 87
(September, 2017), ISBN 9783959770491 [doi] [abs]
 Agarwal, PK; Kumar, N; Sintos, S; Suri, S, Efficient algorithms for kregret minimizing sets,
Leibniz International Proceedings in Informatics, Lipics, vol. 75
(August, 2017), ISBN 9783959770361 [doi] [abs]
 Agarwal, PK; Fox, K; Panigrahi, D; Varadarajan, KR; Xiao, A, Faster algorithms for the geometric transportation problem,
Leibniz International Proceedings in Informatics, Lipics, vol. 77
(June, 2017),
pp. 71716, ISBN 9783959770385 [doi] [abs]
 Wu, Y; Agarwal, PK; Li, C; Yang, J; Yu, C, Computational Fact Checking through Query Perturbations,
Acm Transactions on Database Systems, vol. 42 no. 1
(January, 2017),
pp. 141 [doi]
 Wu, Y; Gao, J; Agarwal, PK; Yang, J, Finding diverse, highvalue representatives on a surface of answers,
Proceedings of the Vldb Endowment, vol. 10 no. 7
(January, 2017),
pp. 793804 [abs]
 Garg, N; Sadiq, M; Agarwal, P, GOASREP: Goal oriented approach for software requirements elicitation and prioritization using analytic hierarchy process,
Advances in Intelligent Systems and Computing, vol. 516
(January, 2017),
pp. 281287, ISBN 9789811031557 [doi] [abs]
Arlotto, Alessandro
 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, vol. 20 no. 3
(September, 2018),
pp. 839854 [doi] [abs]
 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 & Algorithms, vol. 52 no. 1
(January, 2018),
pp. 4153, Wiley [doi] [abs]
 Arlotto, A; Xie, X, Logarithmic regret in the dynamic and stochastic knapsack problem.,
Corr, vol. abs/1809.02016
(2018)
 Arlotto, A; Frazelle, AE; Wei, Y, Strategic open routing in service networks,
Management Science
(2018), INFORMS
 Arlotto, A; Gurvich, I, Uniformly bounded regret in the multisecretary problem
(October, 2017) [abs]
Autry, Eric A.
 Autry, EA; Bayliss, A; Volpert, VA, Biological control with nonlocal interactions,
Mathematical Biosciences, vol. 301
(July, 2018),
pp. 129146 [doi]
 Autry, EA; Bayliss, A; Volpert, VA, Traveling waves in a nonlocal, piecewise linear reaction–diffusion population model,
Nonlinearity, vol. 30 no. 8
(August, 2017),
pp. 33043331 [doi]
Bendich, Paul L
 Garagić, D; Peskoe, J; Liu, F; Claffey, MS; Bendich, P; Hineman, J; Borggren, N; Harer, J; Zulch, P; Rhodes, BJ, Upstream fusion of multiple sensing modalities using machine learning and topological analysis: An initial exploration,
Ieee Aerospace Conference Proceedings, vol. 2018March
(June, 2018),
pp. 18, ISBN 9781538620144 [doi] [abs]
 Tralie, CJ; Smith, A; Borggren, N; Hineman, J; Bendich, P; Zulch, P; Harer, J, Geometric CrossModal Comparison of Heterogeneous Sensor Data,
Proceedings of the 39th IEEE Aerospace Conference
(March, 2018) [abs]
Bertozzi, Andrea L
 J. B. Greer and A. L. Bertozzi, H1 solutions of a class of fourth order nonlinear equations for image processing,
Discrete And Continuous Dynamical Systems, vol. 10 no. 12
(2004),
pp. 349  366
Bray, Hubert
 Bray, H; Roesch, H, Proof of a Null Geometry Penrose Conjecture,
Notices of the American Mathematical Society., vol. 65
(February, 2018), American Mathematical Society
Bryant, Robert
(search)
 Bryant, R; 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. 345357 [doi]
Calderbank, Robert
 Thompson, A; Calderbank, R, Sparse nearequiangular tight frames with applications in full duplex wireless communication,
2017 Ieee Global Conference on Signal and Information Processing, Globalsip 2017 Proceedings, vol. 2018January
(March, 2018),
pp. 868872, ISBN 9781509059904 [doi] [abs]
 Mappouras, G; Vahid, A; Calderbank, R; Hower, DR; Sorin, DJ, Jenga: Efficient fault tolerance for stacked DRAM,
Proceedings  35th IEEE International Conference on Computer Design, ICCD 2017
(November, 2017),
pp. 361368, ISBN 9781538622544 [doi] [abs]
 Kadhe, S; Calderbank, R, Rate optimal binary linear locally repairable codes with small availability,
Ieee International Symposium on Information Theory Proceedings
(August, 2017),
pp. 166170, ISBN 9781509040964 [doi] [abs]
 Michelusi, N; Nokleby, M; Mitra, U; Calderbank, R, Multiscale spectrum sensing in smallcell mmwave cognitive wireless networks,
Ieee International Conference on Communications
(July, 2017), ISBN 9781467389990 [doi] [abs]
 CnaanOn, I; Harms, A; Krolik, JL; Calderbank, AR, Runlength limited codes for backscatter communication,
2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp)
(June, 2017),
pp. 61106114, ISBN 9781509041176 [doi] [abs]
 Wang, L; Chen, M; Rodrigues, M; Wilcox, D; Calderbank, R; Carin, L, InformationTheoretic Compressive Measurement Design.,
Ieee Transactions on Pattern Analysis and Machine Intelligence, vol. 39 no. 6
(June, 2017),
pp. 11501164 [doi] [abs]
 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, Wcnc
(May, 2017), ISBN 9781509041831 [doi] [abs]
 Campbell, K; Carpenter, KLH; Espinosa, S; Hashemi, J; Qiu, Q; Tepper, M; Calderbank, R; Sapiro, G; Egger, HL; Baker, JP; Dawson, G, Use of a Digital Modified Checklist for Autism in Toddlers  Revised with Followup to Improve Quality of Screening for Autism.,
The Journal of Pediatrics, vol. 183
(April, 2017),
pp. 133139.e1 [doi] [abs]
Cheng, Cheng
 Cheng, C; Jiang, Y; Sun, Q, Spatially distributed sampling and reconstruction,
Applied and Computational Harmonic Analysis
(August, 2017) [doi]
 Li, L; Cheng, C; Han, D; Sun, Q; Shi, G, Phase Retrieval From MultipleWindow ShortTime Fourier Measurements,
Ieee Signal Processing Letters, vol. 24 no. 4
(April, 2017),
pp. 372376 [doi]
Cheng, Xiuyuan
 Lu, J; Lu, Y; Wang, X; Li, X; Linderman, GC; Wu, C; Cheng, X; Mu, L; Zhang, H; Liu, J; Su, M; Zhao, H; Spatz, ES; Spertus, JA; Masoudi, FA; Krumholz, HM; Jiang, L, Prevalence, awareness, treatment, and control of hypertension in China: data from 1·7 million adults in a populationbased screening study (China PEACE Million Persons Project),
Lancet (London, England), vol. 390 no. 10112
(December, 2017),
pp. 25492558 [doi]
 Cheng, X; Mishne, G; Steinerberger, S, The geometry of nodal sets and outlier detection,
Journal of Number Theory
(October, 2017) [doi]
Dasgupta, Samit
 Dasgupta, S; Voight, J, Sylvester’s problem and mock Heegner points,
Proceedings of the American Mathematical Society, vol. 146 no. 8
(March, 2018),
pp. 32573273 [doi]
Daubechies, Ingrid
 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.,
Anatomical Record (Hoboken, N.J. : 2007), vol. 301 no. 4
(April, 2018),
pp. 636658 [doi] [abs]
 Xu, J; Yang, H; Daubechies, I, Recursive diffeomorphismbased regression for shape functions,
Siam Journal on Mathematical Analysis, vol. 50 no. 1
(January, 2018),
pp. 532 [doi] [abs]
 Alaifari, R; Daubechies, I; Grohs, P; Thakur, G, Reconstructing RealValued Functions from Unsigned Coefficients with Respect to Wavelet and Other Frames,
Journal of Fourier Analysis and Applications, vol. 23 no. 6
(December, 2017),
pp. 14801494 [doi]
 Deligiannis, N; Mota, JFC; Cornelis, B; Rodrigues, MRD; Daubechies, I, MultiModal Dictionary Learning for Image Separation With Application in Art Investigation,
Ieee Transactions on Image Processing : a Publication of the Ieee Signal Processing Society, vol. 26 no. 2
(February, 2017),
pp. 751764 [doi]
 Cornelis, B; Yang, H; Goodfriend, A; Ocon, N; Lu, J; Daubechies, I, Removal of Canvas Patterns in Digital Acquisitions of Paintings.,
Ieee Transactions on Image Processing : a Publication of the Ieee Signal Processing Society, vol. 26 no. 1
(January, 2017),
pp. 160171 [doi] [abs]
 Voronin, S; Daubechies, I, An iteratively reweighted least squares algorithm for sparse regularization,
in Contemporary Mathematics, vol. 693
(January, 2017),
pp. 391411 [doi] [abs]
 Yin, R; Gao, T; Lu, YM; Daubechies, I, A Tale of Two Bases: LocalNonlocal Regularization on Image Patches with Convolution Framelets,
Siam Journal on Imaging Sciences, vol. 10 no. 2
(January, 2017),
pp. 711750 [doi]
 Fodor, G; Cornelis, B; Yin, R; Dooms, A; Daubechies, I, Cradle Removal in XRay Images of Panel Paintings,
Image Processing On Line, vol. 7
(2017),
pp. 2342 [doi]
Dolbow, John E.
 Zhang, Z; Jiang, W; Dolbow, JE; Spencer, BW, A modified momentfitted integration scheme for XFEM applications with historydependent material data,
Computational Mechanics, vol. 62 no. 2
(August, 2018),
pp. 233252 [doi] [abs]
 Peco, C; Liu, Y; Rhea, C; Dolbow, JE, Models and simulations of surfactantdriven fracture in particle rafts,
International Journal of Solids and Structures
(January, 2018) [doi] [abs]
 Peco, C; Chen, W; Liu, Y; Bandi, MM; Dolbow, JE; Fried, E, Influence of surface tension in the surfactantdriven fracture of closelypacked particulate monolayers.,
Soft Matter, vol. 13 no. 35
(September, 2017),
pp. 58325841 [doi] [abs]
 Zhang, Z; Dolbow, JE, Remeshing strategies for large deformation problems with frictional contact and nearly incompressible materials,
International Journal for Numerical Methods in Engineering, vol. 109 no. 9
(March, 2017),
pp. 12891314 [doi]
 Stershic, AJ; Dolbow, JE; Moës, N, The Thick LevelSet model for dynamic fragmentation,
Engineering Fracture Mechanics, vol. 172
(March, 2017),
pp. 3960 [doi]
Dunson, David B.
(search)
 Srivastava, S; Li, C; Dunson, DB, Scalable Bayes via barycenter in Wasserstein space,
Journal of Machine Learning Research, vol. 19
(August, 2018),
pp. 135 [abs]
 Shterev, ID; Dunson, DB; Chan, C; Sempowski, GD, Bayesian MultiPlate HighThroughput Screening of Compounds.,
Scientific Reports, vol. 8 no. 1
(June, 2018),
pp. 9551 [doi] [abs]
 Johndrow, JE; Lum, K; Dunson, DB, Theoretical limits of microclustering for record linkage.,
Biometrika, vol. 105 no. 2
(June, 2018),
pp. 431446 [doi] [abs]
 Miller, JW; Dunson, DB, Robust Bayesian inference via coarsening,
Journal of the American Statistical Association
(May, 2018),
pp. 131 [doi]
 Zhang, Z; Descoteaux, M; Zhang, J; Girard, G; Chamberland, M; Dunson, D; Srivastava, A; Zhu, H, Mapping populationbased structural connectomes.,
Neuroimage, vol. 172
(May, 2018),
pp. 130145 [doi] [abs]
 van den Boom, W; Schroeder, RA; Manning, MW; Setji, TL; Fiestan, GO; Dunson, DB, Effect of A1C and Glucose on Postoperative Mortality in Noncardiac and Cardiac Surgeries.,
Diabetes Care, vol. 41 no. 4
(April, 2018),
pp. 782788 [doi] [abs]
 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
(January, 2018),
pp. 113 [doi] [abs]
 Dunson, DB, Statistics in the big data era: Failures of the machine,
Statistics & Probability Letters
(January, 2018) [doi] [abs]
 Bertrán, MA; Martínez, NL; Wang, Y; Dunson, D; Sapiro, G; Ringach, D, Active learning of cortical connectivity from twophoton imaging data.,
Plos One, vol. 13 no. 5
(January, 2018),
pp. e0196527 [doi] [abs]
 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. 140 [abs]
 Wheeler, MW; Dunson, DB; Herring, AH, Bayesian Local Extremum Splines.,
Biometrika, vol. 104 no. 4
(December, 2017),
pp. 939952, Oxford University Press (OUP) [abs]
 Shang, Y; Dunson, D; Song, JS, Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics,
Operations Research, vol. 65 no. 6
(December, 2017),
pp. 15741588 [doi]
 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. 15471552 [doi]
 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. 15161530 [doi] [abs]
 Reddy, A; Zhang, J; Davis, NS; Moffitt, AB; Love, CL; Waldrop, A; Leppa, S; Pasanen, A; Meriranta, L; KarjalainenLindsberg, ML; 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; BernalMizrachi, 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; AuYeung, RKH; Kwong, YL; 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. 481494.e15 [doi] [abs]
 Li, C; Srivastava, S; Dunson, DB, Simple, scalable and accurate posterior interval estimation,
Biometrika, vol. 104 no. 3
(September, 2017),
pp. 665680 [doi] [abs]
 Lock, EF; Dunson, DB, Bayesian genome and epigenomewide association studies with gene level dependence.,
Biometrics, vol. 73 no. 3
(September, 2017),
pp. 10181028 [doi] [abs]
 Srivastava, S; Engelhardt, BE; Dunson, DB, Expandable factor analysis.,
Biometrika, vol. 104 no. 3
(September, 2017),
pp. 649663 [doi] [abs]
 Guhaniyogi, R; Qamar, S; Dunson, DB, Bayesian tensor regression,
Journal of Machine Learning Research, vol. 18
(August, 2017),
pp. 131 [abs]
 Schaich Borg, J; Srivastava, S; Lin, L; Heffner, J; Dunson, D; Dzirasa, K; de Lecea, L, Rat intersubjective decisions are encoded by frequencyspecific oscillatory contexts.,
Brain and Behavior, vol. 7 no. 6
(June, 2017),
pp. e00710 [doi] [abs]
 Zhu, B; Dunson, DB, Bayesian Functional Data Modeling for Heterogeneous Volatility,
Bayesian Analysis, vol. 12 no. 2
(June, 2017),
pp. 335350 [doi]
 Wang, L; Durante, D; Jung, RE; Dunson, DB, Bayesian networkresponse regression.,
Bioinformatics (Oxford, England), vol. 33 no. 12
(June, 2017),
pp. 18591866 [doi] [abs]
 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. 561576 [doi] [abs]
 Ovaskainen, O; Tikhonov, G; Dunson, D; Grøtan, V; Engen, S; Sæther, BE; Abrego, N, How are species interactions structured in speciesrich communities? A new method for analysing timeseries data.,
Proceedings of the Royal Society B: Biological Sciences, vol. 284 no. 1855
(May, 2017),
pp. 2017076820170768 [doi] [abs]
 Moffitt, AB; Ondrejka, SL; McKinney, M; Rempel, RE; Goodlad, JR; Teh, CH; Leppa, S; Mannisto, S; Kovanen, PE; Tse, E; AuYeung, RKH; Kwong, YL; 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, Enteropathyassociated T cell lymphoma subtypes are characterized by loss of function of SETD2.,
The Journal of Experimental Medicine, vol. 214 no. 5
(May, 2017),
pp. 13711386 [doi] [abs]
 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. 555580 [doi]
 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; DelfauLarue, MH; Fataccioli, V; Czader, MB; Lossos, IS; ChapmanFredricks, JR; Richards, KL; Fedoriw, Y; Ondrejka, SL; Hsi, ED; Low, L; Weisenburger, D; Chan, WC; MehtaShah, N; Horwitz, S; BernalMizrachi, L; Flowers, CR; Beaven, AW; Parihar, M; Baseggio, L; Parrens, M; Moreau, A; Sujobert, P; Pilichowska, M; Evens, AM; Chadburn, A; AuYeung, RKH; Srivastava, G; Choi, WWL; Goodlad, JR; Aurer, I; BasicKinda, 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 Tcell Lymphoma.,
Cancer Discovery, vol. 7 no. 4
(April, 2017),
pp. 369379 [doi] [abs]
 Tikhonov, G; Abrego, N; Dunson, D; Ovaskainen, O, Using joint species distribution models for evaluating how speciestospecies associations depend on the environmental context, edited by Warton, D,
Methods in Ecology and Evolution, vol. 8 no. 4
(April, 2017),
pp. 443452 [doi]
 Dunson, DB, Toward Automated Prior Choice,
Statistical Science, vol. 32 no. 1
(February, 2017),
pp. 4143 [doi]
 Abrego, N; Dunson, D; Halme, P; Salcedo, I; Ovaskainen, O, Woodinhabiting fungi with tight associations with other species have declined as a response to forest management,
Oikos, vol. 126 no. 2
(February, 2017) [doi]
 Johndrow, JE; Bhattacharya, A; Dunson, DB, TENSOR DECOMPOSITIONS AND SPARSE LOGLINEAR MODELS.,
The Annals of Statistics, vol. 45 no. 1
(January, 2017),
pp. 138 [doi] [abs]
 Lin, L; St Thomas, B; Zhu, H; Dunson, DB, Extrinsic local regression on manifoldvalued data.,
Journal of the American Statistical Association, vol. 112 no. 519
(January, 2017),
pp. 12611273 [doi] [abs]
 Durante, D; Dunson, DB; Vogelstein, JT, Nonparametric Bayes Modeling of Populations of Networks,
Journal of the American Statistical Association, vol. 112 no. 520
(2017),
pp. 15161530 [doi]
 Lin, L; Rao, V; Dunson, D, Bayesian nonparametric inference on the Stiefel manifold,
Statistica Sinica
(2017) [doi]
Durrett, Richard T.
 Ma, R; Durrett, R, A simple evolutionary game arising from the study of the role of igfII in pancreatic cancer,
The Annals of Applied Probability, vol. 28 no. 5
(October, 2018),
pp. 28962921 [doi] [abs]
 Wang, Z; Durrett, R, Extrapolating weak selection in evolutionary games.,
Journal of Mathematical Biology
(July, 2018) [doi] [abs]
 Gleeson, JP; Durrett, R, Temporal profiles of avalanches on networks,
Nature Communications, vol. 8 no. 1
(December, 2017) [doi]
 Lopatkin, AJ; Meredith, HR; Srimani, JK; Pfeiffer, C; Durrett, R; You, L, Persistence and reversal of plasmidmediated antibiotic resistance.,
Nature Communications, vol. 8 no. 1
(November, 2017),
pp. 1689 [doi] [abs]
 Tomasetti, C; Durrett, R; Kimmel, M; Lambert, A; Parmigiani, G; Zauber, A; Vogelstein, B, Role of stemcell divisions in cancer risk,
Nature, vol. 548 no. 7666
(August, 2017),
pp. E13E14 [doi]
 Huo, R; Durrett, R, Latent voter model on locally treelike random graphs,
Stochastic Processes and Their Applications
(August, 2017) [doi]
 Nanda, M; Durrett, R, Spatial evolutionary games with weak selection,
Proceedings of the National Academy of Sciences of the United States of America, vol. 114 no. 23
(June, 2017),
pp. 60466051 [doi]
 Bessonov, M; Durrett, R, Phase transitions for a planar quadratic contact process,
Advances in Applied Mathematics, vol. 87
(June, 2017),
pp. 82107 [doi]
Dym, Nadav
 Lazar, R; Dym, N; Kushinsky, Y; Huang, Z; Ju, T; Lipman, Y, Robust optimization for topological surface reconstruction.,
Acm Trans. Graph., vol. 37
(2018),
pp. 46:146:1 [doi]
 Dym, N; Maron, H; Lipman, Y, DS++,
Acm Transactions on Graphics, vol. 36 no. 6
(November, 2017),
pp. 114 [doi]
 Maron, H; Galun, M; Aigerman, N; Trope, M; Dym, N; Yumer, E; Kim, VG; Lipman, Y, Convolutional neural networks on surfaces via seamless toric covers,
Acm Transactions on Graphics, vol. 36 no. 4
(July, 2017),
pp. 110 [doi]
 Dym, N; Lipman, Y, Exact Recovery with Symmetries for Procrustes Matching,
Siam Journal on Optimization, vol. 27 no. 3
(January, 2017),
pp. 15131530 [doi]
 Dym, N; Lipman, Y; Slutsky, R, A Linear Variational Principle for Riemann Mapping and Discrete Conformality.,
Corr, vol. abs/1711.02221
(2017)
Fernandes de Oliveira, Goncalo M.
 Oliveira, G, Gerbes on G2 manifolds,
Journal of Geometry and Physics, vol. 114
(April, 2017),
pp. 570580 [doi]
Getz, Jayce R.
 Getz, JR, Nonabelian fourier transforms for spherical representations,
Pacific Journal of Mathematics, vol. 294 no. 2
(January, 2018),
pp. 351373, Mathematical Sciences Publishers [doi] [abs]
Hain, Richard
(search)
 Brown, F; Hain, R, Algebraic de Rham theory for weakly holomorphic modular forms of level one,
Algebra & Number Theory, vol. 12 no. 3
(2018),
pp. 723750 [doi]
 Hain, R, DeligneBeilinson Cohomology of Affine Groups,
in Hodge Theory and $L^2$analysis, edited by Ji, L
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Harer, John
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Pfister, Henry
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Ieee International Symposium on Information Theory Proceedings, vol. 2018June
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Ieee Transactions on Information Theory
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2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
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 Jian, YY; Pfister, HD; Narayanan, KR, Approaching Capacity at High Rates with Iterative HardDecision Decoding,
Ieee Transactions on Information Theory
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pp. 11 [doi]
Pierce, Lillian B.
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Revista Matemática Iberoamericana
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Computer Physics Communications
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Trends in Biotechnology, vol. 35 no. 11
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 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]
 Dabagh, M; Jalali, P; Butler, PJ; Randles, A; Tarbell, JM, Mechanotransmission in endothelial cells subjected to oscillatory and multidirectional shear flow.,
Journal of the Royal Society, Interface, vol. 14 no. 130
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 Gounley, J; Draeger, EW; Randles, A, Numerical simulation of a compound capsule in a constricted microchannel.,
Procedia Computer Science, vol. 108
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 Laurence, TA; Ly, S; Fong, E; Shusteff, M; Randles, A; Gounley, J; Draeger, E, Using stroboscopic flow imaging to validate largescale computational fluid dynamics simulations,
Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10076
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Reed, Michael C.
 West, A; Best, J; Abdalla, A; Nijhout, F; Reed, M; Hashemi, P, Voltammetric evidence for discrete serotonin circuits, linked to specific reuptake domains, in the mouse medial prefrontal cortex.,
Neurochemistry International
(July, 2018) [doi] [abs]
 Duncan, W; Best, J; Golubitsky, M; Nijhout, HF; Reed, M, Homeostasis despite instability.,
Mathematical Biosciences, vol. 300
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 Suppiramaniam, V; Bloemer, J; Reed, M; Bhattacharya, S, Neurotransmitter Receptors,
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 Best, J; Nijhout, HF; Samaranayake, S; Hashemi, P; Reed, M, A mathematical model for histamine synthesis, release, and control in varicosities.,
Theoretical Biology & Medical Modelling, vol. 14 no. 1
(December, 2017),
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 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),
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 Nijhout, HF; SadreMarandi, F; Best, J; Reed, MC, Systems Biology of Phenotypic Robustness and Plasticity.,
Integrative and Comparative Biology, vol. 57 no. 2
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 Reed, MC; Best, J; Nijhout, HF, Mathematical models of neuromodulation and implications for neurology and psychiatry, edited by Erdi, P; Battacharya, B; Cochran, A
(2017)
 Reed, MC; Lawley, S; Nijhout, HF, Spiracular fluttering increases oxygen uptake
(2017)
 Reed, MC; Best, J; Nijhout, HF, Mathematical models of neuromodulation and implications for neurology and psychiatry,
in Computational Neurology and Psychiatry, edited by Erdi, P; Bhattacharya, B; Cochran, A
(2017), SPRINGER
 Thanacoody, HKR; Nijhout, HF; Reed, MC; Thomas, S, Mathematical modeling of the effect of different intravenous acetylcysteine regimens on hepatic glutathione regeneration and hepatocyte death following simulated acetaminophen overdose,
Clinical Toxicology (Philadelphia, Pa.), vol. 55 no. 7
(2017),
pp. 753753
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Clinical Toxicology (Philadelphia, Pa.), vol. 55 no. 7
(2017),
pp. 753754
Robles, Colleen M
 Robles, C, Characterization of Calabi–Yau variations of Hodge structure over tube domains by characteristic forms,
Mathematische Annalen
(September, 2017),
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 Kerr, M; Robles, C, Variations of Hodge structure and orbits in flag varieties,
Advances in Mathematics, vol. 315
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 Kerr, M; Robles, C, Classification of smooth horizontal Schubert varieties,
European Journal of Mathematics, vol. 3 no. 2
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Rudin, Cynthia D.
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The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 38 no. 7
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 Angelino, E; LarusStone, N; Alabi, D; Seltzer, M; Rudin, C, Learning certifiably optimal rule lists for categorical data,
Journal of Machine Learning Research, vol. 18
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Jama Neurology, vol. 74 no. 12
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 Ustun, B; Rudin, C, Optimized risk scores,
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, vol. Part F129685
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 Angelino, E; LarusStone, N; Alabi, D; Seltzer, M; Rudin, C, Learning certifiably optimal rule lists,
Proceedings of the Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, vol. Part F129685
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 Wang, T; Rudin, C; DoshiVelez, F; Liu, Y; Klampfl, E; MacNeille, P, A Bayesian framework for learning rule sets for interpretable classification,
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 Letham, B; Letham, PA; Rudin, C; Browne, EP, Erratum: "Prediction uncertainty and optimal experimental design for learning dynamical systems" [Chaos 26, 063110 (2016)].,
Chaos (Woodbury, N.Y.), vol. 27 no. 6
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 Zeng, J; Ustun, B; Rudin, C, Interpretable classification models for recidivism prediction,
Journal of the Royal Statistical Society: Series a (Statistics in Society), vol. 180 no. 3
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 Ustun, B; Adler, LA; Rudin, C; Faraone, SV; Spencer, TJ; Berglund, P; Gruber, MJ; Kessler, RC, The World Health Organization Adult AttentionDeficit/Hyperactivity Disorder SelfReport Screening Scale for DSM5.,
Jama Psychiatry, vol. 74 no. 5
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 Wang, T; Rudin, C; VelezDoshi, F; Liu, Y; Klampfl, E; Macneille, P, Bayesian rule sets for interpretable classification,
Proceedings Ieee International Conference on Data Mining, Icdm
(January, 2017),
pp. 12691274, ISBN 9781509054725 [doi] [abs]
 Yang, H; Rudin, C; Seltzer, M, Scalable Bayesian rule lists,
34th International Conference on Machine Learning, Icml 2017, vol. 8
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Ryser, Marc D.
 Ryser, MD; Min, BH; Siegmund, KD; Shibata, D, Spatial mutation patterns as markers of early colorectal tumor cell mobility.,
Proceedings of the National Academy of Sciences of the United States of America, vol. 115 no. 22
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Saper, Leslie
 Saper, L, ℒmodules and microsupport,
to appear in Annals of Mathematics
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 Saper, L, Perverse sheaves and the reductive BorelSerre compactification,
in Hodge Theory and L²analysis, edited by Ji, L, vol. 39
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Sapiro, Guillermo
 Hashemi, J; Dawson, G; Carpenter, KLH; Campbell, K; Qiu, Q; Espinosa, S; Marsan, S; Baker, JP; Egger, HL; Sapiro, G, Computer Vision Analysis for Quantification of Autism Risk Behaviors,
Ieee Transactions on Affective Computing
(August, 2018) [doi] [abs]
 Bartesaghi, A; Aguerrebere, C; Falconieri, V; Banerjee, S; Earl, LA; Zhu, X; Grigorieff, N; Milne, JLS; Sapiro, G; Wu, X; Subramaniam, S, Atomic Resolution CryoEM Structure of βGalactosidase.,
Structure (London, England : 1993), vol. 26 no. 6
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 Giryes, R; Eldar, YC; Bronstein, AM; Sapiro, G, Tradeoffs Between Convergence Speed and Reconstruction Accuracy in Inverse Problems,
Ieee Transactions on Signal Processing, vol. 66 no. 7
(April, 2018),
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 Campbell, K; Carpenter, KL; Hashemi, J; Espinosa, S; Marsan, S; Borg, JS; Chang, Z; Qiu, Q; Vermeer, S; Adler, E; Tepper, M; Egger, HL; Baker, JP; Sapiro, G; Dawson, G, Computer vision analysis captures atypical attention in toddlers with autism.,
Autism
(March, 2018),
pp. 1362361318766247 [doi] [abs]
 Vu, MAT; Adalı, T; Ba, D; Buzsáki, G; Carlson, D; Heller, K; Liston, C; Rudin, C; Sohal, VS; Widge, AS; Mayberg, HS; Sapiro, G; Dzirasa, K, A Shared Vision for Machine Learning in Neuroscience.,
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, vol. 38 no. 7
(February, 2018),
pp. 16011607 [doi] [abs]
 Pisharady, PK; Sotiropoulos, SN; DuarteCarvajalino, JM; Sapiro, G; Lenglet, C, Estimation of white matter fiber parameters from compressed multiresolution diffusion MRI using sparse Bayesian learning.,
Neuroimage, vol. 167
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 Qiu, Q; Hashemi, J; Sapiro, G, Intelligent synthesis driven model calibration: framework and face recognition application,
Proceedings 2017 Ieee International Conference on Computer Vision Workshops, Iccvw 2017, vol. 2018January
(January, 2018),
pp. 25642572, ISBN 9781538610343 [doi] [abs]
 Sokolić, J; Qiu, Q; Rodrigues, MRD; Sapiro, G, Learning to identify while failing to discriminate,
Proceedings 2017 Ieee International Conference on Computer Vision Workshops, Iccvw 2017, vol. 2018January
(January, 2018),
pp. 25372544, ISBN 9781538610343 [doi] [abs]
 Bertrán, MA; Martínez, NL; Wang, Y; Dunson, D; Sapiro, G; Ringach, D, Active learning of cortical connectivity from twophoton imaging data.,
Plos One, vol. 13 no. 5
(January, 2018),
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 Asiedu, MN; Simhal, A; Lam, CT; Mueller, J; Chaudhary, U; Schmitt, JW; Sapiro, G; Ramanujam, N, Image processing and machine learning techniques to automate diagnosis of Lugol's iodine cervigrams for a lowcost pointofcare digital colposcope,
Progress in Biomedical Optics and Imaging Proceedings of Spie, vol. 10485
(January, 2018), ISBN 9781510614550 [doi] [abs]
 Chiew, KS; Hashemi, J; Gans, LK; Lerebours, L; Clement, NJ; Vu, MAT; Sapiro, G; Heller, NE; Adcock, RA, Motivational valence alters memory formation without altering exploration of a reallife spatial environment.,
Plos One, vol. 13 no. 3
(January, 2018),
pp. e0193506 [doi] [abs]
 Duchin, Y; Shamir, RR; Patriat, R; Kim, J; Vitek, JL; Sapiro, G; Harel, N, Patientspecific anatomical model for deep brain stimulation based on 7 Tesla MRI.,
Plos One, vol. 13 no. 8
(January, 2018),
pp. e0201469 [doi] [abs]
 Lezama, J; Qiu, Q; Sapiro, G, Not afraid of the dark: NIRVIS face recognition via crossspectral hallucination and lowrank embedding,
Proceedings 30th Ieee Conference on Computer Vision and Pattern Recognition, Cvpr 2017, vol. 2017January
(November, 2017),
pp. 68076816 [doi] [abs]
 Ye, Q; Zhang, T; Ke, W; Qiu, Q; Chen, J; Sapiro, G; Zhang, B, Selflearning scenespecific pedestrian detectors using a progressive latent model,
Proceedings 30th Ieee Conference on Computer Vision and Pattern Recognition, Cvpr 2017, vol. 2017January
(November, 2017),
pp. 20572066 [doi] [abs]
 Su, S; Delbracio, M; Wang, J; Sapiro, G; Heidrich, W; Wang, O, Deep video deblurring for handheld cameras,
Proceedings 30th Ieee Conference on Computer Vision and Pattern Recognition, Cvpr 2017, vol. 2017January
(November, 2017),
pp. 237246, ISBN 9781538604571 [doi] [abs]
 Tepper, M; Sapiro, G, Nonnegative matrix underapproximation for robust multiple model fitting,
Proceedings 30th Ieee Conference on Computer Vision and Pattern Recognition, Cvpr 2017, vol. 2017January
(November, 2017),
pp. 655663, ISBN 9781538604571 [doi] [abs]
 Pisharady, PK; Sotiropoulos, SN; Sapiro, G; Lenglet, C, A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multishell Diffusion MRI.,
Medical image computing and computerassisted intervention : MICCAI ... International Conference on Medical Image Computing and ComputerAssisted Intervention, vol. 10433
(September, 2017),
pp. 602610, ISBN 9783319661810 [doi] [abs]
 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. 147151, ISBN 9781538615652 [doi] [abs]
 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),
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 Simhal, AK; Aguerrebere, C; Collman, F; Vogelstein, JT; Micheva, KD; Weinberg, RJ; Smith, SJ; Sapiro, G, Probabilistic fluorescencebased synapse detection.,
Plos Computational Biology, vol. 13 no. 4
(April, 2017),
pp. e1005493 [doi] [abs]
 Campbell, K; Carpenter, KLH; Espinosa, S; Hashemi, J; Qiu, Q; Tepper, M; Calderbank, R; Sapiro, G; Egger, HL; Baker, JP; Dawson, G, Use of a Digital Modified Checklist for Autism in Toddlers  Revised with Followup to Improve Quality of Screening for Autism.,
The Journal of Pediatrics, vol. 183
(April, 2017),
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 Chen, J; Chang, Z; Qiu, Q; Li, X; Sapiro, G; Bronstein, A; Pietikäinen, M, RealSense = real heart rate: Illumination invariant heart rate estimation from videos,
2016 6th International Conference on Image Processing Theory, Tools and Applications, IPTA 2016
(January, 2017), ISBN 9781467389105 [doi] [abs]
 Gunalan, K; Chaturvedi, A; Howell, B; Duchin, Y; Lempka, SF; Patriat, R; Sapiro, G; Harel, N; McIntyre, CC, Creating and parameterizing patientspecific deep brain stimulation pathwayactivation models using the hyperdirect pathway as an example.,
Plos One, vol. 12 no. 4
(January, 2017),
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