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06/13/2020
Hindsight Expectation Maximization for Goal-conditioned Reinforcement Learning
We propose a graphical model framework for goal-conditioned RL, with an ...
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05/29/2019
Variance Reduction for Evolution Strategies via Structured Control Variates
Evolution Strategies (ES) are a powerful class of blackbox optimization ...
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11/30/2017
Variational Deep Q Network
We propose a framework that directly tackles the probability distributio...
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10/31/2016
Edward: A library for probabilistic modeling, inference, and criticism
Probabilistic modeling is a powerful approach for analyzing empirical in...
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06/13/2016
Robust Probabilistic Modeling with Bayesian Data Reweighting
Probabilistic models analyze data by relying on a set of assumptions. Da...
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05/24/2016
Posterior Dispersion Indices
Probabilistic modeling is cyclical: we specify a model, infer its poster...
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03/02/2016
Automatic Differentiation Variational Inference
Probabilistic modeling is iterative. A scientist posits a simple model, ...
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01/04/2016
Variational Inference: A Review for Statisticians
One of the core problems of modern statistics is to approximate difficul...
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06/10/2015
Automatic Variational Inference in Stan
Variational inference is a scalable technique for approximate Bayesian i...
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11/02/2014