David Dunson
16 papers · 2011–2024 · 3 conferences · across top CS/AI conferences
Achievements
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Conferences
AISTATS (10)
ICML (5)
JMLR (1)
Top co-authors
Keywords
bayesian inference
(6)
hierarchical model
(3)
gibbs sampling
(3)
nonparametric bayesian
(2)
distributed learning
(2)
density estimation
(2)
dictionary learning
(2)
variational inference
(2)
ridge regression
(1)
data augmentation
(1)
dirichlet process
(1)
topic modeling
(1)
logistic regression
(1)
model selection
(1)
low-rank decomposition
(1)
posterior sampling
(1)
covariance estimation
(1)
tensor decomposition
(1)
image denoising
(1)
principal component analysis
(1)
Papers
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
ICML 2024
Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference
AISTATS 2021
Fiedler Regularization: Learning Neural Networks with Graph Sparsity
ICML 2020
Variational Gaussian Copula Inference
AISTATS 2016
No penalty no tears: Least squares in high-dimensional linear models
ICML 2016
Scalable geometric density estimation
AISTATS 2016
WASP: Scalable Bayes via barycenters of subset posteriors
AISTATS 2015
Scalable and Robust Bayesian Inference via the Median Posterior
ICML 2014
Bayesian Logistic Gaussian Process Models for Dynamic Networks
AISTATS 2014
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
ICML 2014
Bayesian learning of joint distributions of objects
AISTATS 2013
Diagonal Orthant Multinomial Probit Models
AISTATS 2013
Beta-Negative Binomial Process and Poisson Factor Analysis
AISTATS 2012
Hierarchical Latent Dictionaries for Models of Brain Activation
AISTATS 2012
Logistic Stick-Breaking Process
JMLR 2011
Dependent Hierarchical Beta Process for Image Interpolation and Denoising
AISTATS 2011