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David M. Blei

44 papers · 2003–2024 · 8 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (8) 🧭 Keyword Pioneer πŸƒ Academic Marathon (21) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) 🌍 Conference Polyglot (8) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (29) 🏠 Conference Loyalist (24) 🌟 Keyword Trendsetter Combo (4) πŸ† Keyword Champion (10) πŸ”¬ Deep Specialist (18) 🌱 Topic Pioneer πŸ—ƒοΈ Keyword Collector (100) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter ❓ The Questioner πŸ’Ž Century Club (44) πŸ”₯ Unstoppable (7)

Conferences

NIPS (24) JMLR (9) AISTATS (3) ICML (3) UAI (2) ICLR (1) MLHC (1) NAACL (1)

Top co-authors

Chong Wang (6) Yixin Wang (5) Claudia Shi (4) Alp Kucukelbir (3) Sean Gerrish (3) Jordan L. Boyd-graber (2) Chirag Modi (2) Charles C. Margossian (2) Edoardo M. Airoldi (2) Dustin Tran (2)

Keywords

variational inference (16) bayesian inference (7) topic modeling (7) bayesian nonparametrics (6) topic model (6) latent dirichlet allocation (6) large language model (4) hierarchical dirichlet process (4) latent variable (4) probabilistic model (4) probabilistic modeling (3) causal inference (3) online learning (3) bayesian nonparametric (3) dirichlet process (3) stochastic optimization (3) gibbs sampling (3) stochastic blockmodel (3) stochastic gradient descent (2) hierarchical model (2)

Papers

EigenVI: score-based variational inference with orthogonal function expansions NIPS 2024
Amortized Variational Inference: When and Why? UAI 2024
Optimization-based Causal Estimation from Heterogeneous Environments JMLR 2024
Hypothesis Testing the Circuit Hypothesis in LLMs NIPS 2024
Evaluating the Moral Beliefs Encoded in LLMs NIPS 2023
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models NIPS 2023
Data Augmentations for Improved (Large) Language Model Generalization NIPS 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions NIPS 2023
Variational Inference with Gaussian Score Matching NIPS 2023
Posterior Collapse and Latent Variable Non-identifiability NIPS 2021
Invariant representation learning for treatment effect estimation UAI 2021
Markovian Score Climbing: Variational Inference with KL(p||q) NIPS 2020
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data AISTATS 2019
Avoiding Latent Variable Collapse with Generative Skip Models AISTATS 2019
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records MLHC 2019
Implicit Causal Models for Genome-wide Association Studies ICLR 2018
Stochastic Gradient Descent as Approximate Bayesian Inference JMLR 2017
Evaluating Bayesian Models with Posterior Dispersion Indices ICML 2017
Zero-Inflated Exponential Family Embeddings ICML 2017
Robust Probabilistic Modeling with Bayesian Data Reweighting ICML 2017
Automatic Differentiation Variational Inference JMLR 2017
Stochastic Variational Inference JMLR 2013
Truncation-free Online Variational Inference for Bayesian Nonparametric Models NIPS 2012
How They Vote: Issue-Adjusted Models of Legislative Behavior NIPS 2012
Scalable Inference of Overlapping Communities NIPS 2012
Spatial distance dependent Chinese restaurant processes for image segmentation NIPS 2011
Distance Dependent Chinese Restaurant Processes JMLR 2011
Dirichlet Process Mixtures of Generalized Linear Models JMLR 2011
Online Variational Inference for the Hierarchical Dirichlet Process AISTATS 2011
Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable NIPS 2010
Online Learning for Latent Dirichlet Allocation NIPS 2010
Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces NIPS 2010
Variational Inference for Adaptor Grammars NAACL 2010
A Bayesian Analysis of Dynamics in Free Recall NIPS 2009
Variational Inference for the Nested Chinese Restaurant Process NIPS 2009
Decoupling Sparsity and Smoothness in the Discrete Hierarchical Dirichlet Process NIPS 2009
Reading Tea Leaves: How Humans Interpret Topic Models NIPS 2009
Mixed Membership Stochastic Blockmodels JMLR 2008
Syntactic Topic Models NIPS 2008
Mixed Membership Stochastic Blockmodels NIPS 2008
Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation NIPS 2008
Supervised Topic Models NIPS 2007
Latent Dirichlet Allocation JMLR 2003
Matching Words and Pictures JMLR 2003