71 citations · 243 across the 20 of their papers we have counts for
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stat.ML2019★ 2 cited
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
Hao Wu, Heiko Zimmermann, Eli Sennesh +2
We develop amortized population Gibbs (APG) samplers, a class of scalable methods that frames structured variational inference as adaptive importance sampling. APG samplers constru…
cs.LG2019★ 4 cited
The Thermodynamic Variational Objective
Vaden Masrani, Tuan Anh Le, Frank Wood
We introduce the thermodynamic variational objective (TVO) for learning in both continuous and discrete deep generative models. The TVO arises from a key connection between variati…
cs.LG2019★ 1 cited
Imitation Learning of Factored Multi-agent Reactive Models
Michael Teng, Tuan Anh Le, Adam Scibior +1
We apply recent advances in deep generative modeling to the task of imitation learning from biological agents. Specifically, we apply variations of the variational recurrent neural…