Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations H Lee, R Grosse, R Ranganath, AY Ng Proceedings of the 26th annual international conference on machine learning …, 2009 | 2337 | 2009 |
Black box variational inference R Ranganath, S Gerrish, D Blei Artificial Intelligence and Statistics, 814-822, 2014 | 523 | 2014 |
Unsupervised learning of hierarchical representations with convolutional deep belief networks H Lee, R Grosse, R Ranganath, AY Ng Communications of the ACM 54 (10), 95-103, 2011 | 322 | 2011 |
Automatic differentiation variational inference A Kucukelbir, D Tran, R Ranganath, A Gelman, DM Blei The Journal of Machine Learning Research 18 (1), 430-474, 2017 | 245 | 2017 |
Hierarchical variational models R Ranganath, D Tran, D Blei International Conference on Machine Learning, 324-333, 2016 | 148 | 2016 |
Backprop kf: Learning discriminative deterministic state estimators T Haarnoja, A Ajay, S Levine, P Abbeel Advances in Neural Information Processing Systems, 4376-4384, 2016 | 133* | 2016 |
Automatic variational inference in Stan A Kucukelbir, R Ranganath, A Gelman, D Blei Advances in neural information processing systems, 568-576, 2015 | 133 | 2015 |
Hierarchical implicit models and likelihood-free variational inference D Tran, R Ranganath, D Blei Advances in Neural Information Processing Systems, 5523-5533, 2017 | 128* | 2017 |
Deep exponential families R Ranganath, L Tang, L Charlin, D Blei Artificial Intelligence and Statistics, 762-771, 2015 | 106 | 2015 |
The variational Gaussian process D Tran, R Ranganath, DM Blei arXiv preprint arXiv:1511.06499, 2015 | 98 | 2015 |
The variational Gaussian process D Tran, R Ranganath, DM Blei arXiv preprint arXiv:1511.06499, 2015 | 98 | 2015 |
Extracting social meaning: Identifying interactional style in spoken conversation D Jurafsky, R Ranganath, D McFarland Proceedings of Human Language Technologies: The 2009 Annual Conference of …, 2009 | 88 | 2009 |
It's not you, it's me: detecting flirting and its misperception in speed-dates R Ranganath, D Jurafsky, D McFarland Proceedings of the 2009 Conference on Empirical Methods in Natural Language …, 2009 | 87 | 2009 |
Bayesian nonparametric poisson factorization for recommendation systems P Gopalan, FJ Ruiz, R Ranganath, D Blei Artificial Intelligence and Statistics, 275-283, 2014 | 82 | 2014 |
An adaptive learning rate for stochastic variational inference R Ranganath, C Wang, B David, E Xing International Conference on Machine Learning, 298-306, 2013 | 75 | 2013 |
Dynamic poisson factorization L Charlin, R Ranganath, J McInerney, DM Blei Proceedings of the 9th ACM Conference on Recommender Systems, 155-162, 2015 | 70 | 2015 |
Variational sequential monte carlo CA Naesseth, SW Linderman, R Ranganath, DM Blei arXiv preprint arXiv:1705.11140, 2017 | 69 | 2017 |
Deep survival analysis R Ranganath, A Perotte, N Elhadad, D Blei arXiv preprint arXiv:1608.02158, 2016 | 67 | 2016 |
Detecting friendly, flirtatious, awkward, and assertive speech in speed-dates R Ranganath, D Jurafsky, DA McFarland Computer Speech & Language 27 (1), 89-115, 2013 | 61 | 2013 |
Risk prediction for chronic kidney disease progression using heterogeneous electronic health record data and time series analysis A Perotte, R Ranganath, JS Hirsch, D Blei, N Elhadad Journal of the American Medical Informatics Association 22 (4), 872-880, 2015 | 50 | 2015 |