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
3286 2009 Black box variational inference R Ranganath, S Gerrish, D Blei
Artificial intelligence and statistics, 814-822, 2014
1109 2014 Automatic differentiation variational inference A Kucukelbir, D Tran, R Ranganath, A Gelman, DM Blei
Journal of machine learning research, 2017
697 2017 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
466 2011 Clinicalbert: Modeling clinical notes and predicting hospital readmission K Huang, J Altosaar, R Ranganath
arXiv preprint arXiv:1904.05342, 2019
456 2019 Hierarchical variational models R Ranganath, D Tran, D Blei
International conference on machine learning, 324-333, 2016
321 2016 Hierarchical implicit models and likelihood-free variational inference D Tran, R Ranganath, D Blei
Advances in Neural Information Processing Systems 30, 2017
317 * 2017 Backprop kf: Learning discriminative deterministic state estimators T Haarnoja, A Ajay, S Levine, P Abbeel
Advances in neural information processing systems 29, 2016
306 * 2016 Automatic variational inference in Stan A Kucukelbir, R Ranganath, A Gelman, D Blei
Advances in neural information processing systems 28, 2015
268 2015 Variational sequential monte carlo C Naesseth, S Linderman, R Ranganath, D Blei
International conference on artificial intelligence and statistics, 968-977, 2018
195 2018 Deep survival analysis R Ranganath, A Perotte, N Elhadad, D Blei
Machine Learning for Healthcare Conference, 101-114, 2016
190 2016 The variational Gaussian process D Tran, R Ranganath, DM Blei
arXiv preprint arXiv:1511.06499, 2015
180 2015 The variational Gaussian process D Tran, R Ranganath, DM Blei
arXiv preprint arXiv:1511.06499, 2015
180 2015 A review of challenges and opportunities in machine learning for health M Ghassemi, T Naumann, P Schulam, AL Beam, IY Chen, R Ranganath
AMIA Summits on Translational Science Proceedings 2020, 191, 2020
162 2020 Variational Inference via AB Dieng, D Tran, R Ranganath, J Paisley, D Blei
Advances in Neural Information Processing Systems 30, 2017
149 2017 Deep exponential families R Ranganath, L Tang, L Charlin, D Blei
Artificial Intelligence and Statistics, 762-771, 2015
148 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
135 2009 Support and invertibility in domain-invariant representations FD Johansson, D Sontag, R Ranganath
arXiv preprint arXiv:1903.03448, 2019
134 2019 Bayesian nonparametric poisson factorization for recommendation systems P Gopalan, FJ Ruiz, R Ranganath, D Blei
Artificial Intelligence and Statistics, 275-283, 2014
125 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
117 2013 