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stat.ML2017★ 84 cited
Deep Probabilistic Programming
Dustin Tran, Matthew D. Hoffman, Rif A. Saurous +3
We propose Edward, a Turing-complete probabilistic programming language. Edward defines two compositional representations---random variables and inference. By treating inference as…
stat.ML2014★ 8 cited
Beta Process Non-negative Matrix Factorization with Stochastic Structured Mean-Field Variational Inference
Dawen Liang, Matthew D. Hoffman
Beta process is the standard nonparametric Bayesian prior for latent factor model. In this paper, we derive a structured mean-field variational inference algorithm for a beta proce…