Deep Probabilistic Programming, Dustin Tran, Matthew D. Hoffman, Rif A. Saurous, Eugene Brevdo, Kevin Murphy, David M. Blei
- Multi-talker Speech Separation and Tracing with Permutation Invariant Training of Deep Recurrent Neural Networks, Morten Kolbæk, Dong Yu, Zheng-Hua Tan, Jesper Jensen
- Constraints versus Priors, Philip B. Stark
- Forecasting at Scale, Sean J. Taylor and Benjamin Letham
- Asymptotically exact inference in differentiable generative models, Matthew Graham, Amos Storkey
- Judgment under Uncertainty: Heuristics and Biases, Amos Tversky, Daniel Kahneman