← Authors

David Blei

71 papers · 2007–2025 · 12 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) πŸƒ Academic Marathon (18) 🌍 Conference Polyglot (12) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (24) 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (21) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (23) πŸ† Keyword Champion (24) 🀝 Dynamic Duo (14) πŸ”₯ Unstoppable (16) ❓ The Questioner πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (102) πŸ’Ž Century Club (71) πŸš€ Conference Pioneer ⚑ Prolific Year (9)

Conferences

NIPS (21) AISTATS (19) ICML (12) UAI (5) EMNLP (4) ACL (2) CLEAR (2) SEMEVAL (2) CONLL (1) ICLR (1) JMLR (1) MLHC (1)

Top co-authors

Rajesh Ranganath (14) Yixin Wang (6) Dustin Tran (5) Francisco Ruiz (5) Achille Nazaret (4) Claudia Shi (4) Scott Linderman (4) Prem Gopalan (4) Stephan Mandt (4) Keyon Vafa (3)

Research topics

Bayesian & Probabilistic (1)

Keywords

variational inference (24) bayesian inference (12) posterior approximation (6) stochastic variational inference (6) causal inference (5) stochastic optimization (5) latent variable model (5) probabilistic model (4) poisson factorization (3) community detection (3) word embedding (3) posterior inference (3) uncertainty quantification (3) bayesian nonparametric (3) representation learning (3) markov chain monte carlo (3) probabilistic modeling (3) posterior distribution (3) gaussian process (3) bayesian nonparametrics (2)

Papers

Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective ICLR 2025
HDP-Flow: Generalizable Bayesian Nonparametric Model for Time Series State Discovery UAI 2025
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference AISTATS 2025
Density Uncertainty Layers for Reliable Uncertainty Estimation AISTATS 2024
Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees NIPS 2024
Stable Differentiable Causal Discovery ICML 2024
Batch and match: black-box variational inference with a score-based divergence ICML 2024
Extremely Greedy Equivalence Search UAI 2024
On the Misspecification of Linear Assumptions in Synthetic Controls AISTATS 2024
A causality-inspired plus-minus model for player evaluation in team sports CLEAR 2024
Estimating the Hallucination Rate of Generative AI NIPS 2024
An Invariant Learning Characterization of Controlled Text Generation ACL 2023
Probabilistic Conformal Prediction Using Conditional Random Samples AISTATS 2023
On the Assumptions of Synthetic Control Methods AISTATS 2022
Forget-me-not! Contrastive critics for mitigating posterior collapse UAI 2022
Variational Inference for Infinitely Deep Neural Networks ICML 2022
Estimating Social Influence from Observational Data CLEAR 2022
A general linear-time inference method for Gaussian Processes on one dimension JMLR 2021
Hierarchical Inducing Point Gaussian Process for Inter-domian Observations AISTATS 2021
A Proxy Variable View of Shared Confounding ICML 2021
variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference UAI 2021
Rationales for Sequential Predictions EMNLP 2021
Unsupervised Representation Learning via Neural Activation Coding ICML 2021
Adapting Text Embeddings for Causal Inference UAI 2020
Text-Based Ideal Points ACL 2020
Adapting Neural Networks for the Estimation of Treatment Effects NIPS 2019
Variational Bayes under Model Misspecification NIPS 2019
Poisson-Randomized Gamma Dynamical Systems NIPS 2019
Using Embeddings to Correct for Unobserved Confounding in Networks NIPS 2019
Proximity Variational Inference AISTATS 2018
Variational Sequential Monte Carlo AISTATS 2018
Noisin: Unbiased Regularization for Recurrent Neural Networks ICML 2018
Augment and Reduce: Stochastic Inference for Large Categorical Distributions ICML 2018
Black Box FDR ICML 2018
Structured Embedding Models for Grouped Data NIPS 2017
Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems AISTATS 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
Variational Inference via $\chi$ Upper Bound Minimization NIPS 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference NIPS 2017
Context Selection for Embedding Models NIPS 2017
A Variational Analysis of Stochastic Gradient Algorithms ICML 2016
Detecting and Characterizing Events EMNLP 2016
Hierarchical Variational Models ICML 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016
The Generalized Reparameterization Gradient NIPS 2016
Operator Variational Inference NIPS 2016
Exponential Family Embeddings NIPS 2016
Deep Survival Analysis MLHC 2016
Variational Tempering AISTATS 2016
Copula variational inference NIPS 2015
The Population Posterior and Bayesian Modeling on Streams NIPS 2015
Stochastic Structured Variational Inference AISTATS 2015
Automatic Variational Inference in Stan NIPS 2015
Deep Exponential Families AISTATS 2015
Black Box Variational Inference AISTATS 2014
Smoothed Gradients for Stochastic Variational Inference NIPS 2014
A Filtering Approach to Stochastic Variational Inference NIPS 2014
Bayesian Nonparametric Poisson Factorization for Recommendation Systems AISTATS 2014
Content-based recommendations with Poisson factorization NIPS 2014
The Inverse Regression Topic Model ICML 2014
Efficient Online Inference for Bayesian Nonparametric Relational Models NIPS 2013
Modeling Overlapping Communities with Node Popularities NIPS 2013
Stick-Breaking Beta Processes and the Poisson Process AISTATS 2012
Bayesian Checking for Topic Models EMNLP 2011
The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling AISTATS 2011
Dirichlet Process Mixtures of Generalized Linear Models AISTATS 2010
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010
A Topic Model for Word Sense Disambiguation CONLL 2007
PUTOP: Turning Predominant Senses into a Topic Model for Word Sense Disambiguation SEMEVAL 2007
A Topic Model for Word Sense Disambiguation EMNLP 2007
PU-BCD: Exponential Family Models for the Coarse- and Fine-Grained All-Words Tasks SEMEVAL 2007