David Dunson

151 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0003-4942-1597

Duke University

Publications

Adaptive Bayesian regression on data with low intrinsic dimensionality — The Annals of Statistics 2026
Modeling Recurrent Failures on Large Directed Networks — Journal of the American Statistical Association 2025
Bayesian Clustering via Fusing of Localized Densities — Journal of the American Statistical Association 2025
Robustifying Likelihoods by Optimistically Re-weighting Data — Journal of the American Statistical Association 2025
Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis — Journal of the American Statistical Association 2025
Product centred Dirichlet processes for Bayesian multiview clustering — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2025
Exact sampling of spanning trees via fast-forwarded random walks — Biometrika 2025
Bayesian inference for generalized linear models via quasi-posteriors — Biometrika 2025
Inferring synergistic and antagonistic interactions in mixtures of exposures — The Annals of Applied Statistics 2025
Bayesian learning of clinically meaningful sepsis phenotypes in northern Tanzania — The Annals of Applied Statistics 2025
Low-rank longitudinal factor regression with application to chemical mixtures — The Annals of Applied Statistics 2025
Infinite joint species distribution models — Biometrika 2025
Factor pretraining in Bayesian multivariate logistic models — Biometrika 2025
Spatial meshing for general Bayesian multivariate models — Journal of Machine Learning Research 2024 (name-matched, not ORCID-linked)
Spatial predictions on physically constrained domains: Applications to Arctic sea salinity data — The Annals of Applied Statistics 2024
Bayesian Inference on High-Dimensional Multivariate Binary Responses — Journal of the American Statistical Association 2024
Radial neighbours for provably accurate scalable approximations of Gaussian processes — Biometrika 2024
Nearest Neighbor Dirichlet Mixtures — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
Bayesian Pyramids: identifiable multilayer discrete latent structure models for discrete data — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2023
Classification Trees for Imbalanced Data: Surface-to-Volume Regularization — Journal of the American Statistical Association 2023
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
Escaping The Curse of Dimensionality in Bayesian Model-Based Clustering — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
Covariate-Informed Latent Interaction Models: Addressing Geographic & Taxonomic Bias in Predicting Bird–Plant Interactions — Journal of the American Statistical Association 2023
Bayesian Spanning Tree: Estimating the Backbone of the Dependence Graph — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
A generalized Bayes framework for probabilistic clustering — Biometrika 2023
Bayesian Modeling of Sequential Discoveries — Journal of the American Statistical Association 2023
Composite mixture of log-linear models with application to psychiatric studies — The Annals of Applied Statistics 2022
Multivariate mixed membership modeling: Inferring domain-specific risk profiles — The Annals of Applied Statistics 2022
Bayesian semiparametric long memory models for discretized event data — The Annals of Applied Statistics 2022
Generalized infinite factorization models — Biometrika 2022
Spatial Multivariate Trees for Big Data Bayesian Regression — Journal of Machine Learning Research 2022 (name-matched, not ORCID-linked)
Correction to: ‘Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation’ — Biometrika 2022
Efficient manifold approximation with spherelets — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
Graph based Gaussian processes on restricted domains — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
Extended stochastic block models with application to criminal networks — The Annals of Applied Statistics 2022
Soft Tensor Regression — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
Bayesian time-aligned factor analysis of paired multivariate time series — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
Perturbed factor analysis: Accounting for group differences in exposure profiles — The Annals of Applied Statistics 2021
Bayesian joint modeling of chemical structure and dose response curves — The Annals of Applied Statistics 2021
Approximating posteriors with high-dimensional nuisance parameters via integrated rotated Gaussian approximation — Biometrika 2021
Bayesian Factor Analysis for Inference on Interactions — Journal of the American Statistical Association 2021
Bayesian Distance Clustering — Journal of Machine Learning Research 2021 (name-matched, not ORCID-linked)
Efficient posterior sampling for high-dimensional imbalanced logistic regression — Biometrika 2020
The Hastings algorithm at fifty — Biometrika 2020
Comparing and Weighting Imperfect Models Using D-Probabilities — Journal of the American Statistical Association 2020
Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods — Biometrika 2020
Targeted Random Projection for Prediction From High-Dimensional Features — Journal of the American Statistical Association 2020
Report of the Editors—2019 — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2020
Discussion — Journal of the American Statistical Association 2020
Classification via local manifold approximation — Biometrika 2020
Bayesian cumulative shrinkage for infinite factorizations — Biometrika 2020
Identifying main effects and interactions among exposures using Gaussian processes — The Annals of Applied Statistics 2020
Estimating densities with non-linear support by using Fisher–Gaussian kernels — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2020
Bayesian constraint relaxation — Biometrika 2020
Nonparametric graphical model for counts — Journal of Machine Learning Research 2020 (name-matched, not ORCID-linked)
Bayesian Closed Surface Fitting Through Tensor Products — Journal of Machine Learning Research 2020 (name-matched, not ORCID-linked)
Robust Bayesian Inference via Coarsening — Journal of the American Statistical Association 2019
Report of the Editors—2018 — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2019
MCMC for Imbalanced Categorical Data — Journal of the American Statistical Association 2019
Common and individual structure of brain networks — The Annals of Applied Statistics 2019
Nonparametric Bayes Models of Fiber Curves Connecting Brain Regions — Journal of the American Statistical Association 2019
Intrinsic Gaussian processes on complex constrained domains — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2019
Scaling up Data Augmentation MCMC via Calibration — Journal of Machine Learning Research 2018 (name-matched, not ORCID-linked)
Bayesian Semiparametric Mixed Effects Markov Models With Application to Vocalization Syntax — Journal of the American Statistical Association 2018
Theoretical limits of microclustering for record linkage — Biometrika 2018
Scalable Bayes via Barycenter in Wasserstein Space — Journal of Machine Learning Research 2018 (name-matched, not ORCID-linked)
Report of the Editors—2017 — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2018
Fast Moment Estimation for Generalized Latent Dirichlet Models — Journal of the American Statistical Association 2018
Report of the Editors—2016 — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2017
Bayesian inference for Matérn repulsive processes — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2017
Simple, scalable and accurate posterior interval estimation — Biometrika 2017
Expandable factor analysis — Biometrika 2017
Bayesian local extremum splines — Biometrika 2017
Bayesian Tensor Regression — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
Robust and Scalable Bayes via a Median of Subset Posterior Measures — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
Nonparametric Bayes Modeling of Populations of Networks — Journal of the American Statistical Association 2017
Extrinsic Local Regression on Manifold-Valued Data — Journal of the American Statistical Association 2017
Rejoinder: Nonparametric Bayes Modeling of Populations of Networks — Journal of the American Statistical Association 2017
Tensor decompositions and sparse log-linear models — The Annals of Statistics 2017
Exploiting Big Data in Logistics Risk Assessment via Bayesian Nonparametrics — Operations Research 2017
Bayesian inference on quasi-sparse count data — Biometrika 2016
Compressed Gaussian Process for Manifold Regression — Journal of Machine Learning Research 2016 (name-matched, not ORCID-linked)
Bayesian Graphical Models for Multivariate Functional Data — Journal of Machine Learning Research 2016 (name-matched, not ORCID-linked)
Data augmentation for models based on rejection sampling — Biometrika 2016
Locally adaptive dynamic networks — The Annals of Applied Statistics 2016
Bayesian manifold regression — The Annals of Statistics 2016
Nonparametric Bayes inference on conditional independence — Biometrika 2016
Bayesian Nonparametric Modeling of Higher Order Markov Chains — Journal of the American Statistical Association 2016
Bayesian Conditional Tensor Factorizations for High-Dimensional Classification — Journal of the American Statistical Association 2016
Bayesian Factorizations of Big Sparse Tensors — Journal of the American Statistical Association 2015
Marginally specified priors for non-parametric Bayesian estimation — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2015
Shared kernel Bayesian screening — Biometrika 2015
Bayesian Compressed Regression — Journal of the American Statistical Association 2015
Dirichlet–Laplace Priors for Optimal Shrinkage — Journal of the American Statistical Association 2015
Bayesian Nonparametric Covariance Regression — Journal of Machine Learning Research 2015 (name-matched, not ORCID-linked)
Latent factor models for density estimation — Biometrika 2014
Functional clustering in nested designs: Modeling variability in reproductive epidemiology studies — The Annals of Applied Statistics 2014
Locally Adaptive Factor Processes for Multivariate Time Series — Journal of Machine Learning Research 2014 (name-matched, not ORCID-linked)
Posterior contraction in sparse Bayesian factor models for massive covariance matrices — The Annals of Statistics 2014
Enriched Stick-Breaking Processes for Functional Data — Journal of the American Statistical Association 2014

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