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David M. Blei

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

Achievements

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+15 more ↓ 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (29) πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (8) 🐣 Hot Topic Early Bird
🌍 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)

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