84 citations · 226 across the 8 of their papers we have counts for
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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.ML2016★ 35 cited
Scalable Learning of Non-Decomposable Objectives
Elad ET. Eban, Mariano Schain, Alan Mackey +3
Modern retrieval systems are often driven by an underlying machine learning model. The goal of such systems is to identify and possibly rank the few most relevant items for a given…