Artykuły udostępnione publicznie: - David BleiWięcej informacji
Dostępne w jakimś miejscu: 97
Automatic differentiation variational inference
A Kucukelbir, D Tran, R Ranganath, A Gelman, DM Blei
Journal of machine learning research 18 (14), 1-45, 2017
Upoważnienia: US National Science Foundation, US Department of Defense
Topic modeling in embedding spaces
AB Dieng, FJR Ruiz, DM Blei
Transactions of the Association for Computational Linguistics 8, 439-453, 2020
Upoważnienia: US National Science Foundation, US Department of Defense, US National …
Probabilistic topic models
D Blei, L Carin, D Dunson
IEEE signal processing magazine 27 (6), 55-65, 2010
Upoważnienia: US National Institutes of Health
Context, learning, and extinction.
SJ Gershman, DM Blei, Y Niv
Psychological review 117 (1), 197, 2010
Upoważnienia: US National Institutes of Health
Adapting neural networks for the estimation of treatment effects
C Shi, D Blei, V Veitch
Advances in neural information processing systems 32, 2019
Upoważnienia: US National Science Foundation, US Department of Defense, US National …
Modeling user exposure in recommendation
D Liang, L Charlin, J McInerney, DM Blei
Proceedings of the 25th international conference on World Wide Web, 951-961, 2016
Upoważnienia: US National Science Foundation
Hierarchical variational models
R Ranganath, D Tran, D Blei
International conference on machine learning, 324-333, 2016
Upoważnienia: US National Science Foundation
Hierarchical implicit models and likelihood-free variational inference
D Tran, R Ranganath, D Blei
Advances in Neural Information Processing Systems 30, 2017
Upoważnienia: US National Science Foundation, US Department of Defense, Natural Sciences …
The blessings of multiple causes
Y Wang, DM Blei
Journal of the American Statistical Association 114 (528), 1574-1596, 2019
Upoważnienia: US National Science Foundation, US Department of Defense, US National …
Factorization meets the item embedding: Regularizing matrix factorization with item co-occurrence
D Liang, J Altosaar, L Charlin, DM Blei
Proceedings of the 10th ACM conference on recommender systems, 59-66, 2016
Upoważnienia: US National Science Foundation
Shopper
FJR Ruiz, S Athey, DM Blei
The Annals of Applied Statistics 14 (1), 1-27, 2020
Upoważnienia: US National Science Foundation, US Department of Defense, US National …
Bayesian learning and inference in recurrent switching linear dynamical systems
S Linderman, M Johnson, A Miller, R Adams, D Blei, L Paninski
Artificial intelligence and statistics, 914-922, 2017
Upoważnienia: US National Science Foundation, US Department of Energy, US Department of …
Frequentist consistency of variational Bayes
Y Wang, DM Blei
Journal of the American Statistical Association 114 (527), 1147-1161, 2019
Upoważnienia: US Department of Defense
Variational sequential monte carlo
C Naesseth, S Linderman, R Ranganath, D Blei
International conference on artificial intelligence and statistics, 968-977, 2018
Upoważnienia: US Department of Defense, Swedish Research Council
Deep survival analysis
R Ranganath, A Perotte, N Elhadad, D Blei
Machine Learning for Healthcare Conference, 101-114, 2016
Upoważnienia: US National Science Foundation
Avoiding latent variable collapse with generative skip models
AB Dieng, Y Kim, AM Rush, DM Blei
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Upoważnienia: US National Science Foundation, US Department of Defense, US National …
Dynamic embeddings for language evolution
M Rudolph, D Blei
Proceedings of the 2018 world wide web conference, 1003-1011, 2018
Upoważnienia: US Department of Defense
The generalized reparameterization gradient
FR Ruiz, TRC AUEB, D Blei
Advances in neural information processing systems 29, 2016
Upoważnienia: European Commission
Variational Inference via Upper Bound Minimization
AB Dieng, D Tran, R Ranganath, J Paisley, D Blei
Advances in Neural Information Processing Systems 30, 2017
Upoważnienia: US National Science Foundation, US Department of Defense
A variational analysis of stochastic gradient algorithms
S Mandt, M Hoffman, D Blei
International conference on machine learning, 354-363, 2016
Upoważnienia: US National Science Foundation
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