| Topic modeling in embedding spaces AB Dieng, FJR Ruiz, DM Blei Transactions of the Association for Computational Linguistics 8, 439-453, 2020 | 503 | 2020 |
| Discovering faster matrix multiplication algorithms with reinforcement learning A Fawzi, M Balog, A Huang, T Hubert, B Romera-Paredes, M Barekatain, ... Nature 610 (7930), 47-53, 2022 | 307 | 2022 |
| SHOPPER: a probabilistic model of consumer choice with substitutes and complements FJR Ruiz, S Athey, DM Blei | 273 | 2020 |
| The generalized reparameterization gradient FR Ruiz, TRC AUEB, D Blei Advances in neural information processing systems 29, 2016 | 182 | 2016 |
| Counterfactual inference for consumer choice across many prod-uct categories S Athey, D Blei, R Donnelly, F Ruiz AEA Pap. Proc. 108, 64-67, 2017 | 149 | 2017 |
| Exponential family embeddings M Rudolph, F Ruiz, S Mandt, D Blei Advances in Neural Information Processing Systems 29, 2016 | 149 | 2016 |
| Bayesian nonparametric poisson factorization for recommendation systems P Gopalan, FJ Ruiz, R Ranganath, D Blei Artificial Intelligence and Statistics, 275-283, 2014 | 127 | 2014 |
| Reparameterization gradients through acceptance-rejection sampling algorithms C Naesseth, F Ruiz, S Linderman, D Blei Artificial Intelligence and Statistics, 489-498, 2017 | 122 | 2017 |
| The dynamic embedded topic model AB Dieng, FJR Ruiz, DM Blei arXiv preprint arXiv:1907.05545, 2019 | 116 | 2019 |
| Estimating heterogeneous consumer preferences for restaurants and travel time using mobile location data S Athey, D Blei, R Donnelly, F Ruiz, T Schmidt AEA Papers and Proceedings 108, 64-67, 2018 | 96 | 2018 |
| De novo gene signature identification from single‐cell RNA‐seq with hierarchical Poisson factorization HM Levitin, J Yuan, YL Cheng, FJR Ruiz, EC Bush, JN Bruce, P Canoll, ... Molecular systems biology 15 (2), e8557, 2019 | 83 | 2019 |
| A contrastive divergence for combining variational inference and mcmc F Ruiz, M Titsias International Conference on Machine Learning, 5537-5545, 2019 | 79 | 2019 |
| Prescribed generative adversarial networks AB Dieng, FJR Ruiz, DM Blei, MK Titsias arXiv preprint arXiv:1910.04302, 2019 | 62 | 2019 |
| Overdispersed black-box variational inference FJR Ruiz, MK Titsias, DM Blei arXiv preprint arXiv:1603.01140, 2016 | 53 | 2016 |
| Structured embedding models for grouped data M Rudolph, F Ruiz, S Athey, D Blei Advances in neural information processing systems 30, 2017 | 51 | 2017 |
| Unbiased implicit variational inference MK Titsias, F Ruiz The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 50 | 2019 |
| Poisson multi-Bernoulli mapping using Gibbs sampling M Fatemi, K Granström, L Svensson, FJR Ruiz, L Hammarstrand IEEE Transactions on Signal Processing 65 (11), 2814-2827, 2017 | 49 | 2017 |
| A generative model for predicting outcomes in college basketball FJR Ruiz, F Perez-Cruz Journal of Quantitative Analysis in Sports 11 (1), 39-52, 2015 | 49 | 2015 |
| Bayesian nonparametric comorbidity analysis of psychiatric disorders FJR Ruiz, I Valera, C Blanco, F Perez-Cruz Journal of Machine Learning Research 15, 1215-1247, 2014 | 38 | 2014 |
| Counterfactual inference for consumer choice across many product categories R Donnelly, FJR Ruiz, D Blei, S Athey Quantitative Marketing and Economics, 1-39, 2021 | 37 | 2021 |
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
