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David M. Blei — all works

377 works · page 3 of 4 · 201–300 · ← David M. Blei

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  1. CAREER: A Foundation Model for Labor Sequence Data ↗RePEc: Research Papers in Economics · no summary yetKeyon Vafa et al.2022 · 6 citations
  2. Learning with Reflective Likelihoods ↗no summary yetAdji Bousso Dieng et al.2018 · 6 citations
  3. Model Criticism for Bayesian Causal Inference ↗arXiv (Cornell University) · no summary yetDustin Tran et al.2016 · 6 citations
  4. Reweighted Data for Robust Probabilistic Models ↗arXiv (Cornell University) · no summary yetZhaoran Wang, Alp Kucukelbir, David M. Blei2016 · 6 citations
  5. Handbook of mixed membership models and their applications ↗CERN Document Server (European Organization for Nuclear Research) · no summary yetEdoardo M. Airoldi et al.2014 · 6 citations
  6. Applications of latent variable models in modeling influence and decision making ↗no summary yetDavid M. Blei, Sean Gerrish2013 · 6 citations
  7. Discussion on the paper by Handcock, Raftery and Tantrum ↗University of Groningen research database (University of Groningen / Centre for Information Technology) · no summary yetTAB Snijders et al.2007 · 6 citations
  8. Computational Analysis and Visualized Comparison of Style in American Poetry ↗no summary yetDavid M. Kaplan, David M. Blei2006 · 6 citations
  9. Estimating Social Influence from Observational Data ↗arXiv (Cornell University) · no summary yetDhanya Sridhar, Caterina De Bacco, David M. Blei2022 · 5 citations
  10. Identifiable Variational Autoencoders via Sparse Decoding. ↗arXiv (Cornell University) · no summary yetGemma E. Moran et al.2021 · 5 citations
  11. Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections ↗no summary yetAaron Schein et al.2021 · 5 citations
  12. A Digital Field Experiment Reveals Large Effects of Friend-to-Friend Texting on Voter Turnout ↗SSRN Electronic Journal · no summary yetAaron Schein et al.2020 · 5 citations
  13. Augment and Reduce: Stochastic Inference for Large Categorical Distributions ↗arXiv (Cornell University) · no summary yetFrancisco J. R. Ruiz et al.2018 · 5 citations
  14. Zero-Inflated Exponential Family Embeddings ↗International Conference on Machine Learning · no summary yetLiping Liu, David M. Blei2017 · 5 citations
  15. A Tale of Two (Types of) Memberships: Comparing Mixed and Partial Membership with a Continuous Data Example ↗no summary yetEdoardo M. Airoldi et al.2014 · 5 citations
  16. A Nested HDP for Hierarchical Topic Models ↗arXiv (Cornell University) · no summary yetJohn William Paisley et al.2013 · 5 citations
  17. Linguistic extensions of topic models ↗ProQuest LLC eBooks · no summary yetDavid M. Blei, Jordan Lee Boyd-Graber2010 · 5 citations
  18. Estimating wage disparities using foundation models ↗Proceedings of the National Academy of Sciences · no summary yetKeyon Vafa, Susan Carleton Athey, David M. Blei2025 · 4 citations
  19. A Bayesian model of underreporting for sexual assault on college campuses ↗The Annals of Applied Statistics · no summary yetCasey Bradshaw, David M. Blei2024 · 4 citations
  20. Batch and match: black-box variational inference with a score-based divergence ↗arXiv (Cornell University) · no summary yetDiana Cai et al.2024 · 4 citations
  21. Hierarchical Causal Models ↗arXiv (Cornell University) · no summary yetEli N. Weinstein, David M. Blei2024 · 4 citations
  22. Stable Differentiable Causal Discovery ↗arXiv (Cornell University) · no summary yetAchille Nazaret et al.2023 · 4 citations
  23. Mapping interstellar dust with Gaussian processes ↗The Annals of Applied Statistics · no summary yetAndrew C. Miller et al.2022 · 4 citations
  24. Probabilistic Conformal Prediction Using Conditional Random Samples ↗arXiv (Cornell University) · no summary yetZhendong Wang et al.2022 · 4 citations
  25. A Bayesian model of dose-response for cancer drug studies ↗The Annals of Applied Statistics · no summary yetWesley Tansey, Christopher Tosh, David M. Blei2019 · 4 citations
  26. Variational Bayes under Model Misspecification ↗arXiv (Cornell University) · no summary yetZhaoran Wang, David M. Blei2019 · 4 citations
  27. Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data ↗arXiv (Cornell University) · no summary yetVictor Veitch et al.2018 · 4 citations
  28. The Population Posterior and Bayesian Inference on Streams ↗arXiv (Cornell University) · no summary yetMcInerney, James, Rajesh Ranganath, David M. Blei2015 · 4 citations
  29. Population empirical Bayes ↗Uncertainty in Artificial Intelligence · no summary yetAlp Kucukelbir, David M. Blei2015 · 4 citations
  30. The Issue-Adjusted Ideal Point Model ↗arXiv (Cornell University) · no summary yetSean Gerrish, David M. Blei2012 · 4 citations
  31. Introduction to probabilistic topic models ↗no summary yetDavid M. Blei2011 · 4 citations
  32. Distance Dependent Infinite Latent Feature Models ↗arXiv (Cornell University) · no summary yetSamuel J. Gershman, Peter I. Frazier, David M. Blei2011 · 4 citations
  33. The Stick-Breaking Construction of the Beta Process as a Poisson Process ↗arXiv (Cornell University) · no summary yetJohn William Paisley, David M. Blei, Michael I. Jordan2011 · 4 citations
  34. Variational Inference with Gaussian Score Matching ↗neural information processing systems · no summary yetChirag Modi et al.2023 · 3 citations
  35. Density Uncertainty Layers for Reliable Uncertainty Estimation ↗arXiv (Cornell University) · no summary yetYookoon Park, David M. Blei2023 · 3 citations
  36. A general linear-time inference method for Gaussian Processes on one dimension ↗Journal of Machine Learning Research · no summary yetJackson Loper et al.2021 · 3 citations
  37. Double Empirical Bayes Testing ↗International Statistical Review · no summary yetWesley Tansey et al.2020 · 3 citations
  38. Technical perspective: Expressive probabilistic models and scalable method of moments ↗Communications of the ACM · no summary yetDavid M. Blei2018 · 3 citations
  39. Evaluating Bayesian Models with Posterior Dispersion Indices ↗International Conference on Machine Learning · no summary yetAlp Kucukelbir, Zhaoran Wang, David M. Blei2017 · 3 citations
  40. A Filtering Approach to Stochastic Variational Inference ↗no summary yetNeil Houlsby, David M. Blei2015 · 3 citations
  41. A Bayesian Boosting Model ↗arXiv (Cornell University) · no summary yetAlexander Lorbert et al.2012 · 3 citations
  42. Dirichlet Process Mixtures of Generalized Linear Models ↗arXiv (Cornell University) · no summary yetLauren A. Hannah, David M. Blei, Warren B. Powell2009 · 3 citations
  43. Multi-Domain Empirical Bayes for Linearly-Mixed Causal Representations ↗arXiv (Cornell University) · no summary yetBohan Wu, Julius von Kügelgen, David M. Blei2026 · 2 citations
  44. Treeffuser: probabilistic prediction via conditional diffusions with gradient-boosted trees ↗neural information processing systems · no summary yetNicolas Beltran-Velez et al.2024 · 2 citations
  45. Treeffuser: Probabilistic Predictions via Conditional Diffusions with Gradient-Boosted Trees ↗arXiv (Cornell University) · no summary yetNicolas Beltran-Velez et al.2024 · 2 citations
  46. Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport ↗UvA-DARE (University of Amsterdam) · no summary yetLiyi Zhang, David M. Blei, Christian A. Naesseth2022 · 2 citations
  47. On the Assumptions of Synthetic Control Methods ↗RePEc: Research Papers in Economics · no summary yetClaudia Shi et al.2021 · 2 citations
  48. Scalable Topic Modeling: Online Learning, Diagnostics, and Recommendation ↗no summary yetDavid M. Blei2017 · 2 citations
  49. Variational inference with copula augmentation. ↗no summary yetDustin Tran, David M. Blei, Edoardo M. Airoldi2015 · 2 citations
  50. Vouros. Non-parametric estimation of topic hierarchies from texts with hierarchical dirichlet processes ↗no summary yetElias Zavitsanos et al.2011 · 2 citations
  51. Hierarchical Bayesian Models for Applications in Information retrieval ↗no summary yetJ. M. Bernardo et al.2003 · 2 citations
  52. Neural Generalized Mixed-Effects Models ↗arXiv (Cornell University) · no summary yetYuli Slavutsky, Sebastian Salazar, David M. Blei2026 · 1 citation
  53. Robust Representation Learning through Explicit Environment Modeling ↗arXiv (Cornell University) · no summary yetYuli Slavutsky, David M. Blei2026 · 1 citation
  54. Bayesian Empirical Bayes: Simultaneous Inference from Probabilistic Symmetries ↗arXiv (Cornell University) · no summary yetWu, Bohan, Weinstein, Eli N., David M. Blei2025 · 1 citation
  55. Quantifying Uncertainty in the Presence of Distribution Shifts ↗arXiv (Cornell University) · no summary yetYuli Slavutsky, David M. Blei2025 · 1 citation
  56. EigenVI: score-based variational inference with orthogonal function expansions ↗neural information processing systems · no summary yetDiana Cai et al.2024 · 1 citation
  57. Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective ↗arXiv (Cornell University) · no summary yetAndrew Jesson, Nicolas Beltran-Velez, David M. Blei2024 · 1 citation
  58. Estimating the Causal Effects of T Cell Receptors ↗arXiv (Cornell University) · no summary yetEli N. Weinstein, Elizabeth Wood, David M. Blei2024 · 1 citation
  59. Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation ↗arXiv (Cornell University) · no summary yetBo-Han Wu, David M. Blei2024 · 1 citation
  60. azizilab/starfysh: STARFYSH ↗Zenodo (CERN European Organization for Nuclear Research) · no summary yetSiyu He et al.2022 · 1 citation
  61. Forget-me-not! Contrastive Critics for Mitigating Posterior Collapse ↗arXiv (Cornell University) · no summary yetSachit Menon, David M. Blei, Carl Vondrick2022 · 1 citation
  62. Variational Inference for Infinitely Deep Neural Networks ↗arXiv (Cornell University) · no summary yetAchille Nazaret, David M. Blei2022 · 1 citation
  63. A Proxy Variable View of Shared Confounding ↗International Conference on Machine Learning · no summary yetZhaoran Wang, David M. Blei2021 · 1 citation
  64. Hierarchical Inducing Point Gaussian Process for Inter-domian Observations ↗International Conference on Artificial Intelligence and Statistics · no summary yetLuhuan Wu et al.2021 · 1 citation
  65. The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019) ↗arXiv (Cornell University) · no summary yetZhaoran Wang, David M. Blei2019 · 1 citation
  66. Noise-Based Regularizers for Recurrent Neural Networks ↗no summary yetAdji Bousso Dieng et al.2018 · 1 citation
  67. The Markov link method: a nonparametric approach to combine observations from multiple experiments ↗bioRxiv (Cold Spring Harbor Laboratory) · no summary yetJackson Loper et al.2018 · 1 citation
  68. Black Box FDR ↗International Conference on Machine Learning · no summary yetWesley Tansey et al.2018 · 1 citation
  69. Proximity Variational Inference ↗arXiv (Cornell University) · no summary yetJaan Altosaar, Rajesh Ranganath, David M. Blei2017 · 1 citation
  70. Comment ↗Journal of the American Statistical Association · no summary yetDustin Tran, David M. Blei2016 · 1 citation
  71. Non-Parametric Bayesian Analysis of Heterogeneous Data ↗no summary yetDavid M. Blei2013 · 1 citation
  72. Scalable recommendation with Poisson factorization,” arXiv:1311.1704 ↗no summary yetPrem Gopalan, Jake M. Hofman, David M. Blei2013 · 1 citation
  73. A Bayesian Nonparametric Approach to Image Super-resolution ↗arXiv (Cornell University) · no summary yetGungor Polatkan et al.2012 · 1 citation
  74. Dynamic and Supervised Topic Models for Literature-Based Discovery ↗no summary yetDavid M. Blei2011 · 1 citation
  75. A focus on graphical model design and applications to document and image analysis ) ↗no summary yetDavid M. Blei, Lawrence Carin, David Dunson2010 · 1 citation
  76. Panel Discussion ↗Springer eBooks · no summary yetDavid M. Blei2008 · 1 citation
  77. Model Directions, Not Words: Mechanistic Topic Models Using Sparse AutoencodersTransactions of the Association for Computational Linguistics (TACL)Carolina Zheng, Nicolas Beltran-Velez, Sweta Karlekar, et al.2026
  78. Exponential Family Synthetic Controls ↗arXiv (Cornell University) · no summary yetHéctor Rodríguez-Déniz, David M. Blei2026
  79. Worst-case low-rank approximations ↗arXiv (Cornell University) · no summary yetA. Fries et al.2026
  80. Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences ↗arXiv (Cornell University) · no summary yetSweta Karlekar et al.2026
  81. Simulation-Based Empirical Bayes ↗arXiv (Cornell University) · no summary yetXinwei Shen et al.2026
  82. Environment-Robust Representation Learning with Empirical Bayes ↗arXiv (Cornell University) · no summary yetYuli Slavutsky et al.2026
  83. Geometric Causal Models ↗arXiv (Cornell University) · no summary yetEli N. Weinstein, David M. Blei2026
  84. The Illusion of Learning from Observational Data: An Empirical Bayes Perspective ↗arXiv (Cornell University) · no summary yetBohan Wu et al.2026
  85. Fisher meets Feynman: score-based variational inference with a product of experts ↗neural information processing systems · no summary yetDiana Cai et al.2025
  86. The Sequential Nature of Science: Quantifying Learning from a Sequence of Studies ↗arXiv (Cornell University) · no summary yetMikhaeil, Jonas M., Green, Donald P., David M. Blei2025
  87. Additional file 1 of Joint representation and visualization of derailed cell states with Decipher ↗Figshare · no summary yetAchille Nazaret et al.2025
  88. Extremely Greedy Equivalence Search ↗arXiv (Cornell University) · no summary yetAchille Nazaret, David M. Blei2025
  89. Input Adaptive Bayesian Model Averaging ↗arXiv (Cornell University) · no summary yetYuli Slavutsky, Sebastian Salazar, David M. Blei2025
  90. Bayesian Invariance Modeling of Multi-Environment Data ↗arXiv (Cornell University) · no summary yetLuhuan Wu et al.2025
  91. Variational Learning of Disentangled Representations ↗arXiv (Cornell University) · no summary yetSlavutsky, Yuli et al.2025
  92. Posterior Mean Matching: Generative Modeling through Online Bayesian Inference ↗arXiv (Cornell University) · no summary yetSebastian Salazar et al.2024
  93. Multi-environment Topic Models ↗arXiv (Cornell University) · no summary yetDominic Sobhani, Amir Feder, David M. Blei2024
  94. Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes ↗arXiv (Cornell University) · no summary yetBo-Han Wu et al.2024
  95. On the Misspecification of Linear Assumptions in Synthetic Control ↗RePEc: Research Papers in Economics · no summary yetAchille Nazaret, Claudia Shi, David M. Blei2023
  96. Revisiting Topic-Guided Language Models ↗arXiv (Cornell University) · no summary yetCarolina Zheng, Keyon Vafa, David M. Blei2023
  97. The Effect of Friend-to-Friend Text Messaging on Turnout in the 2020 U.S. Midterm Elections ↗OSF Preprints (OSF Preprints) · no summary yetSchein, Aaron, David M. Blei, Green, Don2021
  98. Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference ↗arXiv (Cornell University) · no summary yetAntonio Khalil Moretti et al.2021
  99. Unsupervised Representation Learning via Neural Activation Coding ↗arXiv (Cornell University) · no summary yetYookoon Park et al.2021
  100. Hierarchical Inducing Point Gaussian Process for Inter-domain Observations ↗arXiv (Cornell University) · no summary yetLuhuan Wu et al.2021

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