Blei, David M.

84 publications

UAI 2024 Amortized Variational Inference: When and Why? Charles C. Margossian, David M. Blei

NeurIPS 2024 EigenVI: Score-Based Variational Inference with Orthogonal Function Expansions Diana Cai, Chirag Modi, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul

NeurIPS 2024 Hypothesis Testing the Circuit Hypothesis in LLMs Claudia Shi, Nicolas Beltran-Velez, Achille Nazaret, Carolina Zheng, Adrià Garriga-Alonso, Andrew Jesson, Maggie Makar, David M. Blei

JMLR 2024 Optimization-Based Causal Estimation from Heterogeneous Environments Mingzhang Yin, Yixin Wang, David M. Blei

NeurIPS 2023 Data Augmentations for Improved (Large) Language Model Generalization Amir Feder, Yoav Wald, Claudia Shi, Suchi Saria, David M. Blei

NeurIPS 2023 Evaluating the Moral Beliefs Encoded in LLMs Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei

NeurIPS 2023 Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen, Michel Besserve, Liang Wendong, Luigi Gresele, Armin Kekić, Elias Bareinboim, David M. Blei, Bernhard Schölkopf

NeurIPS 2023 Practical and Asymptotically Exact Conditional Sampling in Diffusion Models Luhuan Wu, Brian Trippe, Christian Naesseth, David M. Blei, John P. Cunningham

NeurIPS 2023 Variational Inference with Gaussian Score Matching Chirag Modi, Robert Gower, Charles Margossian, Yuling Yao, David M. Blei, Lawrence K. Saul

UAI 2021 Invariant Representation Learning for Treatment Effect Estimation Claudia Shi, Victor Veitch, David M. Blei

NeurIPS 2021 Posterior Collapse and Latent Variable Non-Identifiability Yixin Wang, David M. Blei, John P. Cunningham

NeurIPS 2020 Markovian Score Climbing: Variational Inference with KL(p||q) Christian Naesseth, Fredrik Lindsten, David M. Blei

AISTATS 2019 Avoiding Latent Variable Collapse with Generative Skip Models Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei

AISTATS 2019 Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data Victor Veitch, Morgane Austern, Wenda Zhou, David M. Blei, Peter Orbanz

MLHC 2019 The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak

ICLR 2018 Implicit Causal Models for Genome-Wide Association Studies Dustin Tran, David M. Blei

AISTATS 2018 Proximity Variational Inference Jaan Altosaar, Rajesh Ranganath, David M. Blei

AISTATS 2018 Variational Sequential Monte Carlo Christian A. Naesseth, Scott W. Linderman, Rajesh Ranganath, David M. Blei

JMLR 2017 Automatic Differentiation Variational Inference Alp Kucukelbir, Dustin Tran, Rajesh Ranganath, Andrew Gelman, David M. Blei

AISTATS 2017 Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems Scott W. Linderman, Matthew J. Johnson, Andrew C. Miller, Ryan P. Adams, David M. Blei, Liam Paninski

ICLR 2017 Deep Probabilistic Programming Dustin Tran, Matthew D. Hoffman, Rif A. Saurous, Eugene Brevdo, Kevin Murphy, David M. Blei

ICML 2017 Evaluating Bayesian Models with Posterior Dispersion Indices Alp Kucukelbir, Yixin Wang, David M. Blei

AISTATS 2017 Reparameterization Gradients Through Acceptance-Rejection Sampling Algorithms Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei

ICML 2017 Robust Probabilistic Modeling with Bayesian Data Reweighting Yixin Wang, Alp Kucukelbir, David M. Blei

JMLR 2017 Stochastic Gradient Descent as Approximate Bayesian Inference Stephan Mandt, Matthew D. Hoffman, David M. Blei

ICML 2017 Zero-Inflated Exponential Family Embeddings Li-Ping Liu, David M. Blei

UAI 2016 Overdispersed Black-Box Variational Inference Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei

ICLR 2016 Variational Gaussian Process Dustin Tran, Rajesh Ranganath, David M. Blei

AISTATS 2016 Variational Tempering Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David M. Blei

AISTATS 2015 Deep Exponential Families Rajesh Ranganath, Linpeng Tang, Laurent Charlin, David M. Blei

UAI 2015 Population Empirical Bayes Alp Kucukelbir, David M. Blei

UAI 2015 Scalable Recommendation with Hierarchical Poisson Factorization Prem Gopalan, Jake M. Hofman, David M. Blei

AISTATS 2015 Stochastic Structured Variational Inference Matthew D. Hoffman, David M. Blei

UAI 2015 The Survival Filter: Joint Survival Analysis with a Latent Time Series Rajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei

AISTATS 2014 Bayesian Nonparametric Poisson Factorization for Recommendation Systems Prem Gopalan, Francisco J. R. Ruiz, Rajesh Ranganath, David M. Blei

AISTATS 2014 Black Box Variational Inference Rajesh Ranganath, Sean Gerrish, David M. Blei

ICLR 2013 A Nested HDP for Hierarchical Topic Models John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan

JMLR 2013 Bayesian Canonical Correlation Analysis Chong Wang, David M. Blei

JMLR 2013 Stochastic Variational Inference Matthew D. Hoffman, David M. Blei, Chong Wang, John Paisley

NeurIPS 2012 How They Vote: Issue-Adjusted Models of Legislative Behavior Sean Gerrish, David M. Blei

ICML 2012 Nonparametric Variational Inference Samuel Gershman, Matthew D. Hoffman, David M. Blei

NeurIPS 2012 Scalable Inference of Overlapping Communities Prem Gopalan, Sean Gerrish, Michael Freedman, David M. Blei, David M. Mimno

ICML 2012 Sparse Stochastic Inference for Latent Dirichlet Allocation David M. Mimno, Matthew D. Hoffman, David M. Blei

NeurIPS 2012 Truncation-Free Online Variational Inference for Bayesian Nonparametric Models Chong Wang, David M. Blei

ICML 2012 Variational Bayesian Inference with Stochastic Search John W. Paisley, David M. Blei, Michael I. Jordan

JMLR 2011 Dirichlet Process Mixtures of Generalized Linear Models Lauren A. Hannah, David M. Blei, Warren B. Powell

JMLR 2011 Distance Dependent Chinese Restaurant Processes David M. Blei, Peter I. Frazier

AISTATS 2011 Online Variational Inference for the Hierarchical Dirichlet Process Chong Wang, John Paisley, David M. Blei

ICML 2011 Predicting Legislative Roll Calls from Text Sean Gerrish, David M. Blei

NeurIPS 2011 Spatial Distance Dependent Chinese Restaurant Processes for Image Segmentation Soumya Ghosh, Andrei B. Ungureanu, Erik B. Sudderth, David M. Blei

ICML 2011 Variational Inference for Stick-Breaking Beta Process Priors John W. Paisley, Lawrence Carin, David M. Blei

ICML 2010 A Language-Based Approach to Measuring Scholarly Impact Sean Gerrish, David M. Blei

ICML 2010 Bayesian Nonparametric Matrix Factorization for Recorded Music Matthew D. Hoffman, David M. Blei, Perry R. Cook

CVPR 2010 Building and Using a Semantivisual Image Hierarchy Li-Jia Li, Chong Wang, Yongwhan Lim, David M. Blei, Li Fei-Fei

ICML 2010 Distance Dependent Chinese Restaurant Processes David M. Blei, Peter I. Frazier

NeurIPS 2010 Estimating Spatial Layout of Rooms Using Volumetric Reasoning About Objects and Surfaces Abhinav Gupta, Martial Hebert, Takeo Kanade, David M. Blei

NeurIPS 2010 Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable Lauren Hannah, Warren Powell, David M. Blei

NeurIPS 2010 Online Learning for Latent Dirichlet Allocation Matthew Hoffman, Francis R. Bach, David M. Blei

ICML 2010 The IBP Compound Dirichlet Process and Its Application to Focused Topic Modeling Sinead Williamson, Chong Wang, Katherine A. Heller, David M. Blei

NeurIPS 2009 A Bayesian Analysis of Dynamics in Free Recall Richard Socher, Samuel Gershman, Per Sederberg, Kenneth Norman, Adler J. Perotte, David M. Blei

NeurIPS 2009 Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process Chong Wang, David M. Blei

UAI 2009 Multilingual Topic Models for Unaligned Text Jordan L. Boyd-Graber, David M. Blei

NeurIPS 2009 Reading Tea Leaves: How Humans Interpret Topic Models Jonathan Chang, Sean Gerrish, Chong Wang, Jordan L. Boyd-graber, David M. Blei

CVPR 2009 Simultaneous Image Classification and Annotation Chong Wang, David M. Blei, Li Fei-Fei

NeurIPS 2009 Variational Inference for the Nested Chinese Restaurant Process Chong Wang, David M. Blei

UAI 2008 Continuous Time Dynamic Topic Models Chong Wang, David M. Blei, David Heckerman

JMLR 2008 Mixed Membership Stochastic Blockmodels Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing

NeurIPS 2008 Mixed Membership Stochastic Blockmodels Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing

NeurIPS 2008 Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation Indraneel Mukherjee, David M. Blei

NeurIPS 2008 Syntactic Topic Models Jordan L. Boyd-graber, David M. Blei

ICML 2007 Hierarchical Maximum Entropy Density Estimation Miroslav Dudík, David M. Blei, Robert E. Schapire

UAI 2007 Nonparametric Bayes Pachinko Allocation Wei Li, David M. Blei, Andrew McCallum

NeurIPS 2007 Supervised Topic Models Jon D. Mcauliffe, David M. Blei

ICML 2006 Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing

ICML 2006 Dynamic Topic Models David M. Blei, John D. Lafferty

ICML 2006 Panel Discussion David M. Blei

ICML 2006 Statistical Network Analysis: Models, Issues, and New Directions - ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Anna Goldenberg, Eric P. Xing, Alice X. Zheng

NeurIPS 2005 Correlated Topic Models John D. Lafferty, David M. Blei

NeurIPS 2004 Integrating Topics and Syntax Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum

NeurIPS 2004 Sharing Clusters Among Related Groups: Hierarchical Dirichlet Processes Yee W. Teh, Michael I. Jordan, Matthew J. Beal, David M. Blei

ICML 2004 Variational Methods for the Dirichlet Process David M. Blei, Michael I. Jordan

NeurIPS 2003 Hierarchical Topic Models and the Nested Chinese Restaurant Process Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum, David M. Blei

UAI 2002 Learning with Scope, with Application to Information Extraction and Classification David M. Blei, J. Andrew Bagnell, Andrew Kachites McCallum

NeurIPS 2001 Latent Dirichlet Allocation David M. Blei, Andrew Y. Ng, Michael I. Jordan