Publications (31)
Tensor network factorizations: Relationships between brain structural connectomes and traits
Zhengwu Zhang, Genevera I. Allen, Hongtu Zhu +1
Scalable multiscale density estimation
Ye Wang, Antonio Canale, David Dunson
Bayesian crack detection in ultra high resolution multimodal images of paintings
Bruno Cornelis, Yun Yang, Joshua T. Vogelstein +3
Bayesian Mosaic: Parallelizable Composite Posterior
Ye Wang, David Dunson
Finite sample posterior concentration in high-dimensional regression
Nate Strawn, Artin Armagan, Rayan Saab +2
Median Selection Subset Aggregation for Parallel Inference
Xiangyu Wang, Peichao Peng, David Dunson
Bayesian Nonparametric Covariance Regression
Emily Fox, David Dunson
Symmetric Bilinear Regression for Signal Subgraph Estimation
Lu Wang, Zhengwu Zhang, David Dunson
Bayesian factorizations of big sparse tensors
Jing Zhou, Anirban Bhattacharya, Amy Herring +1
Bayesian Watermark Attacks
Ivo Shterev, David Dunson
Parallel inversion of huge covariance matrices
Anjishnu Banerjee, Joshua Vogelstein, David Dunson
No penalty no tears: Least squares in high-dimensional linear models
Xiangyu Wang, David Dunson, Chenlei Leng
Lognormal and Gamma Mixed Negative Binomial Regression
Mingyuan Zhou, Lingbo Li, David Dunson +1
Geometrically Tempered Hamiltonian Monte Carlo
Akihiko Nishimura, David Dunson
Posterior contraction in sparse Bayesian factor models for massive covariance matrices
Debdeep Pati, Anirban Bhattacharya, Natesh S. Pillai +1
Extrinsic Gaussian processes for regression and classification on manifolds
Lizhen Lin, Mu Niu, Pokman Cheung +1
Variable length trajectory compressible hybrid Monte Carlo
Akihiko Nishimura, David Dunson
Data augmentation for models based on rejection sampling
Vinayak Rao, Lizhen Lin, David Dunson
Adaptive posterior convergence rates in non-linear latent variable models
Shuang Zhou, Debdeep Pati, Anirban Bhattacharya +1
Optimal approximating Markov chains for Bayesian inference
James E. Johndrow, Jonathan C. Mattingly, Sayan Mukherjee +1
Efficient Gaussian Process Regression for Large Data Sets
Anjishnu Banerjee, David Dunson, Surya Tokdar
Density Estimation and Classification via Bayesian Nonparametric Learning of Affine Subspaces
Abhishek Bhattacharya, Garritt Page, David Dunson
Beta-Negative Binomial Process and Poisson Factor Analysis
Mingyuan Zhou, Lauren Hannah, David Dunson +1
Anisotropic function estimation using multi-bandwidth Gaussian processes
Anirban Bhattacharya, Debdeep Pati, David Dunson
DECOrrelated feature space partitioning for distributed sparse regression
Xiangyu Wang, David Dunson, Chenlei Leng
Bayesian inference on dependence in multivariate longitudinal data
Hongxia Yang, Fan Li, Enrique F. Schisterman +2
Convex Mixture Regression for Quantitative Risk Assessment
Antonio Canale, Daniele Durante, David Dunson
Common and Individual Structure of Brain Networks
Lu Wang, Zhengwu Zhang, David Dunson
Generalized double Pareto shrinkage
Artin Armagan, David Dunson, Jaeyong Lee
Intrinsic Gaussian processes on complex constrained domains
Mu Niu, Pokman Cheung, Lizhen Lin +3
Reducing over-clustering via the powered Chinese restaurant process
Jun Lu, Meng Li, David Dunson