David B. Dunson

166 papers A* 17A 13B 1C 1Misc 3Journal 115Unranked 16

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerated algorithms for convex and non-convex optimization on manifolds. Mach. Learn. Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson
2025	J	`jnl`	Domain Adaptive Bootstrap Aggregating. IEEE Trans. Signal Process. Meimei Liu, David B. Dunson
2025	J	`jnl`	Nonparametric IPSS: fast, flexible feature selection with false discovery control. Bioinform. Omar Melikechi, David B. Dunson, Jeffrey W. Miller
2025	J	`jnl`	On the Statistical Capacity of Deep Generative Models. CoRR Edric Tam, David B. Dunson
2024	J	`jnl`	Bayesian Joint Additive Factor Models for Multiview Learning. CoRR Niccolo Anceschi, Federico Ferrari, David B. Dunson, Himel Mallick
2024	J	`jnl`	Ellipsoid Fitting With the Cayley Transform. IEEE Trans. Signal Process. Omar Melikechi, David B. Dunson
2024	J	`jnl`	Fast nonparametric feature selection with error control using integrated path stability selection. CoRR Omar Melikechi, David B. Dunson, Jeffrey W. Miller
2024	J	`jnl`	Hierarchical Shrinkage Gaussian Processes: Applications to Computer Code Emulation and Dynamical System Recovery. SIAM/ASA J. Uncertain. Quantification Tao Tang, Simon Mak, David B. Dunson
2024	J	`jnl`	Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	J	`jnl`	Spatial meshing for general Bayesian multivariate models. J. Mach. Learn. Res. Michele Peruzzi, David B. Dunson
2023	J	`jnl`	Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph. J. Mach. Learn. Res. Leo L. Duan, David B. Dunson
2023	J	`jnl`	Bayesian Transfer Learning. CoRR Piotr M. Suder, Jason Xu, David B. Dunson
2023	J	`jnl`	Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data. J. Mach. Learn. Res. Yuqi Gu, Elena E. Erosheva, Gongjun Xu, David B. Dunson
2023	J	`jnl`	Ellipsoid fitting with the Cayley transform. CoRR Omar Melikechi, David B. Dunson
2023	J	`jnl`	Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering. J. Mach. Learn. Res. Noirrit Kiran Chandra, Antonio Canale, David B. Dunson
2023	J	`jnl`	Hierarchical shrinkage Gaussian processes: applications to computer code emulation and dynamical system recovery. CoRR Tao Tang, Simon Mak, David B. Dunson
2023	J	`jnl`	Machine Learning and the Future of Bayesian Computation. CoRR Steven Winter, Trevor Campbell, Lizhen Lin, Sanvesh Srivastava, David B. Dunson
2023	J	`jnl`	Nearest Neighbor Dirichlet Mixtures. J. Mach. Learn. Res. Shounak Chattopadhyay, Antik Chakraborty, David B. Dunson
2023	J	`jnl`	PPA: Principal parcellation analysis for brain connectomes and multiple traits. NeuroImage Rongjie Liu, Meng Li, David B. Dunson
2023	J	`jnl`	Spectral Gap Regularization of Neural Networks. CoRR Edric Tam, David B. Dunson
2022	J	`jnl`	Exponential-Wrapped Distributions on Symmetric Spaces. SIAM J. Math. Data Sci. Emmanuel Chevallier, Didong Li, Yulong Lu, David B. Dunson
2022	J	`jnl`	Gaussian Process Subspace Prediction for Model Reduction. SIAM J. Sci. Comput. Ruda Zhang, Simon Mak, David B. Dunson
2022	J	`jnl`	Multiscale Graph Comparison via the Embedded Laplacian Distance. CoRR Edric Tam, David B. Dunson
2022	J	`jnl`	Outlier detection for multi-network data. Bioinform. Pritam Dey, Zhengwu Zhang, David B. Dunson
2022	J	`jnl`	Spatial Multivariate Trees for Big Data Bayesian Regression. J. Mach. Learn. Res. Michele Peruzzi, David B. Dunson
2021	J	`jnl`	Bayesian Distance Clustering. J. Mach. Learn. Res. Leo L. Duan, David B. Dunson
2021	J	`jnl`	Bayesian time-aligned factor analysis of paired multivariate time series. J. Mach. Learn. Res. Arkaprava Roy, Jana Schaich Borg, David B. Dunson
2021	J	`jnl`	Gaussian Process Subspace Regression for Model Reduction. CoRR Ruda Zhang, Simon Mak, David B. Dunson
2021	J	`jnl`	Graph auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets. NeuroImage Meimei Liu, Zhengwu Zhang, David B. Dunson
2021	J	`jnl`	Inferring Manifolds From Noisy Data Using Gaussian Processes. CoRR David B. Dunson, Nan Wu
2021	J	`jnl`	Monte Carlo Simulation on the Stiefel Manifold via Polar Expansion. J. Comput. Graph. Stat. Michael Jauch, Peter D. Hoff, David B. Dunson
2021	J	`jnl`	Soft Tensor Regression. J. Mach. Learn. Res. Georgia Papadogeorgou, Zhengwu Zhang, David B. Dunson
2021	A	`conf`	Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference. AISTATS Sean Plummer, Shuang Zhou, Anirban Bhattacharya, David B. Dunson, Debdeep Pati
2020	J	`jnl`	Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds. CoRR Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson
2020	J	`jnl`	Bayesian Closed Surface Fitting Through Tensor Products. J. Mach. Learn. Res. Olivier Binette, Debdeep Pati, David B. Dunson
2020	J	`jnl`	Bayesian neural networks and dimensionality reduction. CoRR Deborshee Sen, Theodore Papamarkou, David B. Dunson
2020	A*	`conf`	Fiedler Regularization: Learning Neural Networks with Graph Sparsity. ICML Edric Tam, David B. Dunson
2020	J	`jnl`	Fiedler Regularization: Learning Neural Networks with Graph Sparsity. CoRR Edric Tam, David B. Dunson
2020	J	`jnl`	Projected t-SNE for batch correction. Bioinform. Emanuele Aliverti, Jeffrey L. Tilson, Dayne L. Filer, Benjamin Babcock, Alejandro Colaneri, Jennifer Ocasio, Timothy R. Gershon, Kirk C. Wilhelmsen, David B. Dunson
2020	J	`jnl`	Reproducible Bootstrap Aggregating. CoRR Meimei Liu, David B. Dunson
2020	J	`jnl`	Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference. CoRR Sean Plummer, Shuang Zhou, Anirban Bhattacharya, David B. Dunson, Debdeep Pati
2020	J	`jnl`	Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity. CoRR Austin Talbot, David B. Dunson, Kafui Dzirasa, David E. Carlson
2019	J	`jnl`	Auto-encoding graph-valued data with applications to brain connectomes. CoRR Meimei Liu, Zhengwu Zhang, David B. Dunson
2019	J	`jnl`	Classification via local manifold approximation. CoRR Didong Li, David B. Dunson
2019	J	`jnl`	Efficient Entropy Estimation for Stationary Time Series. CoRR Alexander L. Young, David B. Dunson
2019	J	`jnl`	Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer's Disease. Frontiers Neuroinformatics Alexandra Badea, Wenlin Wu, Jordan Shuff, Michele Wang, Robert J. Anderson, Yi Qi, G. Allan Johnson, Joan G. Wilson, Serge Koudoro, Eleftherios Garyfallidis, Carol A. Colton, David B. Dunson
2019	C	`conf`	Locally Convex Kernel Mixtures: Bayesian Subspace Learning. ICMLA Duy Hoang Thai, Hau-Tieng Wu, David B. Dunson
2019	J	`jnl`	Supervised Multiscale Dimension Reduction for Spatial Interaction Networks. CoRR Shaobo Han, David B. Dunson
2019	J	`jnl`	Symmetric Bilinear Regression for Signal Subgraph Estimation. IEEE Trans. Signal Process. Lu Wang, Zhengwu Zhang, David B. Dunson
2019	J	`jnl`	Tensor network factorizations: Relationships between brain structural connectomes and traits. NeuroImage Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu, David B. Dunson
2018	J	`jnl`	Bayesian Distance Clustering. CoRR Leo L. Duan, David B. Dunson
2018	J	`jnl`	Clustering-Enhanced Stochastic Gradient MCMC for Hidden Markov Models with Rare States. CoRR Rihui Ou, Alexander L. Young, David B. Dunson
2018	J	`jnl`	Extrema-weighted feature extraction for functional data. Bioinform. Willem van den Boom, Callie Mao, Rebecca A. Schroeder, David B. Dunson
2018	J	`jnl`	Intrinsic Gaussian processes on complex constrained domains. CoRR Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson
2018	J	`jnl`	Mapping population-based structural connectomes. NeuroImage Zhengwu Zhang, Maxime Descoteaux, Jingwen Zhang, Gabriel Girard, Maxime Chamberland, David B. Dunson, Anuj Srivastava, Hongtu Zhu
2018	J	`jnl`	Multiresolution Tensor Decomposition for Multiple Spatial Passing Networks. CoRR Shaobo Han, David B. Dunson
2018	J	`jnl`	Non-Oscillatory Pattern Learning for Non-Stationary Signals. CoRR Jieren Xu, Yitong Li, David B. Dunson, Ingrid Daubechies, Haizhao Yang
2018	J	`jnl`	Reducing over-clustering via the powered Chinese restaurant process. CoRR Jun Lu, Meng Li, David B. Dunson
2018	J	`jnl`	Scalable Bayes via Barycenter in Wasserstein Space. J. Mach. Learn. Res. Sanvesh Srivastava, Cheng Li, David B. Dunson
2018	J	`jnl`	Scaling up Data Augmentation MCMC via Calibration. J. Mach. Learn. Res. Leo L. Duan, James E. Johndrow, David B. Dunson
2017	J	`jnl`	Bayesian Tensor Regression. J. Mach. Learn. Res. Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson
2017	J	`jnl`	Bayesian network-response regression. Bioinform. Lu Wang, Daniele Durante, Rex E. Jung, David B. Dunson
2017	J	`jnl`	Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics. Oper. Res. Yan Shang, David B. Dunson, Jing-Sheng Song
2017	J	`jnl`	Robust and Scalable Bayes via a Median of Subset Posterior Measures. J. Mach. Learn. Res. Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
2016	J	`jnl`	Bayesian Graphical Models for Multivariate Functional Data. J. Mach. Learn. Res. Hongxiao Zhu, Nate Strawn, David B. Dunson
2016	J	`jnl`	Boosting Variational Inference. CoRR Fangjian Guo, Xiangyu Wang, Kai Fan, Tamara Broderick, David B. Dunson
2016	J	`jnl`	Compressed Gaussian Process for Manifold Regression. J. Mach. Learn. Res. Rajarshi Guhaniyogi, David B. Dunson
2016	—	`conf`	DECOrrelated feature space partitioning for distributed sparse regression. NIPS Xiangyu Wang, David B. Dunson, Chenlei Leng
2016	J	`jnl`	DECOrrelated feature space partitioning for distributed sparse regression. CoRR Xiangyu Wang, David B. Dunson, Chenlei Leng
2016	J	`jnl`	Fast moment estimation for generalized latent Dirichlet models. CoRR Shiwen Zhao, Barbara E. Engelhardt, Sayan Mukherjee, David B. Dunson
2016	J	`jnl`	Inefficiency of Data Augmentation for Large Sample Imbalanced Data. CoRR James E. Johndrow, Aaron Smith, Natesh S. Pillai, David B. Dunson
2016	A*	`conf`	No penalty no tears: Least squares in high-dimensional linear models. ICML Xiangyu Wang, David B. Dunson, Chenlei Leng
2016	J	`jnl`	Removing Cradle Artifacts in X-Ray Images of Paintings. SIAM J. Imaging Sci. Rujie Yin, Bruno Cornelis, Gábor Fodor, Noelle Ocon, David B. Dunson, Ingrid Daubechies
2016	A	`conf`	Scalable geometric density estimation. AISTATS Ye Wang, Antonio Canale, David B. Dunson
2016	J	`jnl`	Subspace segmentation by dense block and sparse representation. Neural Networks Kewei Tang, David B. Dunson, Zhixun Su, Risheng Liu, Jie Zhang, Jiangxin Dong
2016	A	`conf`	Variational Gaussian Copula Inference. AISTATS Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin
2015	J	`jnl`	A hybrid bayesian approach for genome-wide association studies on related individuals. Bioinform. Akram Yazdani, David B. Dunson
2015	J	`jnl`	Bayesian nonparametric covariance regression. J. Mach. Learn. Res. Emily B. Fox, David B. Dunson
2015	J	`jnl`	No penalty no tears: Least squares in high-dimensional linear models. CoRR Xiangyu Wang, David B. Dunson, Chenlei Leng
2015	—	`conf`	On the consistency theory of high dimensional variable screening. NIPS Xiangyu Wang, Chenlei Leng, David B. Dunson
2015	J	`jnl`	On the consistency theory of high dimensional variable screening. CoRR Xiangyu Wang, Chenlei Leng, David B. Dunson
2015	—	`conf`	Parallelizing MCMC with Random Partition Trees. NIPS Xiangyu Wang, Fangjian Guo, Katherine A. Heller, David B. Dunson
2015	—	`conf`	Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process. NIPS Ye Wang, David B. Dunson
2015	—	`conf`	Quantifying uncertainty in variable selection with arbitrary matrices. CAMSAP Willem van den Boom, David B. Dunson, Galen Reeves
2015	A	`conf`	Uncovering Systematic Bias in Ratings across Categories: a Bayesian Approach. RecSys Fangjian Guo, David B. Dunson
2015	J	`jnl`	Variational Gaussian Copula Inference. CoRR Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin
2015	A	`conf`	WASP: Scalable Bayes via barycenters of subset posteriors. AISTATS Sanvesh Srivastava, Volkan Cevher, Quoc Tran-Dinh, David B. Dunson
2014	J	`jnl`	Adaptive sampling for Bayesian geospatial models. Stat. Comput. Hongxia Yang, Fei Liu, Chunlin Ji, David B. Dunson
2014	J	`jnl`	Bayesian Conditional Density Filtering for Big Data. CoRR Rajarshi Guhaniyogi, Shaan Qamar, David B. Dunson
2014	A	`conf`	Bayesian Logistic Gaussian Process Models for Dynamic Networks. AISTATS Daniele Durante, David B. Dunson
2014	B	`conf`	Digital cradle removal in X-ray images of art paintings. ICIP Rujie Yin, David B. Dunson, Bruno Cornelis, Bill Brown, Noelle Ocon, Ingrid Daubechies
2014	J	`jnl`	Improving prediction from dirichlet process mixtures via enrichment. J. Mach. Learn. Res. Sara Wade, David B. Dunson, Sonia Petrone, Lorenzo Trippa
2014	J	`jnl`	Learning phenotype densities conditional on many interacting predictors. Bioinform. David C. Kessler, Jack A. Taylor, David B. Dunson
2014	J	`jnl`	Locally adaptive factor processes for multivariate time series. J. Mach. Learn. Res. Daniele Durante, Bruno Scarpa, David B. Dunson
2014	—	`conf`	Median Selection Subset Aggregation for Parallel Inference. NIPS Xiangyu Wang, Peichao Peng, David B. Dunson
2014	J	`jnl`	Median Selection Subset Aggregation for Parallel Inference. CoRR Xiangyu Wang, Peichao Peng, David B. Dunson
2014	J	`jnl`	Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling. IEEE Trans. Biomed. Eng. David E. Carlson, Joshua T. Vogelstein, Qisong Wu, Wenzhao Lian, Mingyuan Zhou, Colin R. Stoetzner, Daryl Kipke, Douglas Weber, David B. Dunson, Lawrence Carin
2014	J	`jnl`	Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14). CoRR Laurent Jacques, Christophe De Vleeschouwer, Yannick Boursier, Prasad Sudhakar, C. De Mol, Aleksandra Pizurica, Sandrine Anthoine, Pierre Vandergheynst, Pascal Frossard, Cagdas Bilen, Srdan Kitic, Nancy Bertin, Rémi Gribonval, Nicolas Boumal, Bamdev Mishra, Pierre-Antoine Absil, Rodolphe Sepulchre, Shaun Bundervoet, Colas Schretter, Ann Dooms, Peter Schelkens, Olivier Chabiron, François Malgouyres, Jean-Yves Tourneret, Nicolas Dobigeon, Pierre Chainais, Cédric Richard, Bruno Cornelis, Ingrid Daubechies, David B. Dunson, Marie Danková, Pavel Rajmic, Kévin Degraux, Valerio Cambareri, Bert Geelen, Gauthier Lafruit, Gianluca Setti, Jean-François Determe, Jérôme Louveaux, François Horlin, Angélique Drémeau, Patrick Héas, Cédric Herzet, Vincent Duval, Gabriel Peyré, Alhussein Fawzi, Mike E. Davies, Nicolas Gillis, Stephen A. Vavasis, Charles Soussen, Luc Le Magoarou, Jingwei Liang, Jalal Fadili, Antoine Liutkus, David Martina, Sylvain Gigan, Laurent Daudet, Mauro Maggioni, Stanislav Minsker, Nate Strawn, C. Mory, Fred Maurice Ngolè Mboula, Jean-Luc Starck, Ignace Loris, Samuel Vaiter, Mohammad Golbabaee, Dejan Vukobratovic
2014	J	`jnl`	Robust and scalable Bayes via a median of subset posterior measures. CoRR Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
2014	A*	`conf`	Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. ICML Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David B. Dunson, Lawrence Carin
2014	A*	`conf`	Scalable and Robust Bayesian Inference via the Median Posterior. ICML Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
2014	J	`jnl`	Semiconvex Regression for Metamodeling-Based Optimization. SIAM J. Optim. Lauren A. Hannah, Warren B. Powell, David B. Dunson
2014	J	`jnl`	Special issue on Bayesian computing, methods and applications. Comput. Stat. Data Anal. Cathy W. S. Chen, David B. Dunson, Sylvia Frühwirth-Schnatter, Stephen G. Walker
2013	J	`jnl`	Analysis of space-time relational data with application to legislative voting. Comput. Stat. Data Anal. Esther Salazar, David B. Dunson, Lawrence Carin
2013	J	`jnl`	Bayesian Compressed Regression CoRR Rajarshi Guhaniyogi, David B. Dunson
2013	J	`jnl`	Bayesian Consensus Clustering CoRR Eric F. Lock, David B. Dunson
2013	J	`jnl`	Bayesian consensus clustering. Bioinform. Eric F. Lock, David B. Dunson
2013	J	`jnl`	Bayesian crack detection in ultra high resolution multimodal images of paintings CoRR Bruno Cornelis, Yun Yang, Joshua T. Vogelstein, Ann Dooms, Ingrid Daubechies, David B. Dunson
2013	—	`conf`	Bayesian crack detection in ultra high resolution multimodal images of paintings. DSP Bruno Cornelis, Yun Yang, Joshua T. Vogelstein, Ann Dooms, Ingrid Daubechies, David B. Dunson
2013	A	`conf`	Bayesian learning of joint distributions of objects. AISTATS Anjishnu Banerjee, Jared Murray, David B. Dunson
2013	J	`jnl`	Deep Learning with Hierarchical Convolutional Factor Analysis. IEEE Trans. Pattern Anal. Mach. Intell. Bo Chen, Gungor Polatkan, Guillermo Sapiro, David M. Blei, David B. Dunson, Lawrence Carin
2013	A	`conf`	Diagonal Orthant Multinomial Probit Models. AISTATS James E. Johndrow, David B. Dunson, Kristian Lum
2013	J	`jnl`	Learning Densities Conditional on Many Interacting Features CoRR David C. Kessler, Jack A. Taylor, David B. Dunson
2013	—	`conf`	Locally Adaptive Bayesian Multivariate Time Series. NIPS Daniele Durante, Bruno Scarpa, David B. Dunson
2013	—	`conf`	Multiscale Dictionary Learning for Estimating Conditional Distributions. NIPS Francesca Petralia, Joshua T. Vogelstein, David B. Dunson
2013	J	`jnl`	Multiscale Dictionary Learning for Estimating Conditional Distributions. CoRR Francesca Petralia, Joshua T. Vogelstein, David B. Dunson
2013	J	`jnl`	Multivariate convex regression with adaptive partitioning. J. Mach. Learn. Res. Lauren Hannah, David B. Dunson
2013	J	`jnl`	Parallel MCMC via Weierstrass Sampler. CoRR Xiangyu Wang, David B. Dunson
2013	J	`jnl`	Posterior consistency in conditional distribution estimation. J. Multivar. Anal. Debdeep Pati, David B. Dunson, Surya T. Tokdar
2012	J	`jnl`	Bayesian Watermark Attacks CoRR Ivo Shterev, David B. Dunson
2012	A*	`conf`	Bayesian Watermark Attacks. ICML Ivo Shterev, David B. Dunson
2012	A	`conf`	Beta-Negative Binomial Process and Poisson Factor Analysis. AISTATS Mingyuan Zhou, Lauren Hannah, David B. Dunson, Lawrence Carin
2012	J	`jnl`	Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit Design CoRR Lauren Hannah, David B. Dunson
2012	A*	`conf`	Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit Design. ICML Lauren Hannah, David B. Dunson
2012	A	`conf`	Hierarchical Latent Dictionaries for Models of Brain Activation. AISTATS Alona Fyshe, Emily B. Fox, David B. Dunson, Tom M. Mitchell
2012	J	`jnl`	High Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections. IEEE Signal Process. Mag. Lawrence Carin, Alfred O. Hero III, Joseph E. Lucas, David B. Dunson, Minhua Chen, Ricardo Henao, Arnau Tibau Puig, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg
2012	A*	`conf`	Lognormal and Gamma Mixed Negative Binomial Regression. ICML Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin
2012	J	`jnl`	Lognormal and Gamma Mixed Negative Binomial Regression. CoRR Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin
2012	—	`conf`	Multiresolution Gaussian Processes. NIPS Emily B. Fox, David B. Dunson
2012	J	`jnl`	Nonparametric Bayes classification and hypothesis testing on manifolds. J. Multivar. Anal. Abhishek Bhattacharya, David B. Dunson
2012	J	`jnl`	Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images. IEEE Trans. Image Process. Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Lingbo Li, Zhengming Xing, David B. Dunson, Guillermo Sapiro, Lawrence Carin
2012	—	`conf`	Repulsive Mixtures. NIPS Francesca Petralia, Vinayak A. Rao, David B. Dunson
2012	J	`jnl`	Semiparametric Bayesian local functional models for diffusion tensor tract statistics. NeuroImage Zhaowei Hua, David B. Dunson, John H. Gilmore, Martin Andreas Styner, Hongtu Zhu
2011	A*	`conf`	Approximate Dynamic Programming for Storage Problems. ICML Lauren Hannah, David B. Dunson
2011	J	`jnl`	Bayesian Inference for Genomic Data Integration Reduces Misclassification Rate in Predicting Protein-Protein Interactions. PLoS Comput. Biol. Chuanhua Xing, David B. Dunson
2011	J	`jnl`	Bayesian Local Contamination Models for Multivariate Outliers. Technometrics Garritt L. Page, David B. Dunson
2011	J	`jnl`	Corrections to "Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds". IEEE Trans. Signal Process. Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin
2011	Misc	`conf`	Covariate-dependent dictionary learning and sparse coding. ICASSP Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin
2011	A	`conf`	Dependent Hierarchical Beta Process for Image Interpolation and Denoising. AISTATS Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin
2011	—	`conf`	Generalized Beta Mixtures of Gaussians. NIPS Artin Armagan, David B. Dunson, Merlise A. Clyde
2011	—	`conf`	Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices. NIPS XianXing Zhang, David B. Dunson, Lawrence Carin
2011	J	`jnl`	Learning Low-Dimensional Signal Models. IEEE Signal Process. Mag. Lawrence Carin, Richard G. Baraniuk, Volkan Cevher, David B. Dunson, Michael I. Jordan, Guillermo Sapiro, Michael B. Wakin
2011	J	`jnl`	Logistic Stick-Breaking Process. J. Mach. Learn. Res. Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
2011	A	`conf`	Preface. AISTATS Geoffrey J. Gordon, David B. Dunson
2011	A	`ed.`	Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2011, Fort Lauderdale, USA, April 11-13, 2011 AISTATS Geoffrey J. Gordon, David B. Dunson, Miroslav Dudík
2011	A*	`conf`	The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning. ICML Bo Chen, Gungor Polatkan, Guillermo Sapiro, David B. Dunson, Lawrence Carin
2011	—	`conf`	The Kernel Beta Process. NIPS Lu Ren, Yingjian Wang, David B. Dunson, Lawrence Carin
2011	A*	`conf`	Topic Modeling with Nonparametric Markov Tree. ICML Haojun Chen, David B. Dunson, Lawrence Carin
2011	A*	`conf`	Tree-Structured Infinite Sparse Factor Model. ICML XianXing Zhang, David B. Dunson, Lawrence Carin
2010	J	`jnl`	Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies. BMC Bioinform. Bo Chen, Minhua Chen, John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Alfred O. Hero III, Joseph E. Lucas, David B. Dunson, Lawrence Carin
2010	J	`jnl`	Classification with Incomplete Data Using Dirichlet Process Priors. J. Mach. Learn. Res. Chunping Wang, Xuejun Liao, Lawrence Carin, David B. Dunson
2010	J	`jnl`	Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds. IEEE Trans. Signal Process. Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin
2010	—	`conf`	Joint Analysis of Time-Evolving Binary Matrices and Associated Documents. NIPS Eric Wang, Dehong Liu, Jorge G. Silva, David B. Dunson, Lawrence Carin
2010	J	`jnl`	Probabilistic Topic Models. IEEE Signal Process. Mag. David M. Blei, Lawrence Carin, David B. Dunson
2010	J	`jnl`	Semiparametric Bayes hierarchical models with mean and variance constraints. Comput. Stat. Data Anal. Mingan Yang, David B. Dunson, Donna D. Baird
2009	—	`conf`	A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation. NIPS Lan Du, Lu Ren, David B. Dunson, Lawrence Carin
2009	Misc	`conf`	Multi-task classification with infinite local experts. ICASSP Chunping Wang, Qi An, Lawrence Carin, David B. Dunson
2009	J	`jnl`	Multitask Compressive Sensing. IEEE Trans. Signal Process. Shihao Ji, David B. Dunson, Lawrence Carin
2009	Misc	`conf`	Music analysis with a Bayesian dynamic model. ICASSP Lu Ren, David B. Dunson, Scott Lindroth, Lawrence Carin
2008	A*	`conf`	Hierarchical kernel stick-breaking process for multi-task image analysis. ICML Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin, David B. Dunson
2008	J	`jnl`	Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data. IEEE Trans. Signal Process. Kai Ni, John W. Paisley, Lawrence Carin, David B. Dunson
2008	A*	`conf`	Multi-task compressive sensing with Dirichlet process priors. ICML Yuting Qi, Dehong Liu, David B. Dunson, Lawrence Carin
2008	A*	`conf`	The dynamic hierarchical Dirichlet process. ICML Lu Ren, David B. Dunson, Lawrence Carin
2007	A*	`conf`	Multi-task learning for sequential data via iHMMs and the nested Dirichlet process. ICML Kai Ni, Lawrence Carin, David B. Dunson
2007	A*	`conf`	The matrix stick-breaking process for flexible multi-task learning. ICML Ya Xue, David B. Dunson, Lawrence Carin