2.3k citations · 4.2k across the 44 of their papers we have counts for
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Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
Will Grathwohl, Dami Choi, Yuhuai Wu +2
Gradient-based optimization is the foundation of deep learning and reinforcement learning. Even when the mechanism being optimized is unknown or not differentiable, optimization us…
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Yuhuai Wu, Elman Mansimov, Shun Liao +2
In this work, we propose to apply trust region optimization to deep reinforcement learning using a recently proposed Kronecker-factored approximation to the curvature. We extend th…
Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference
Geoffrey Roeder, Yuhuai Wu, David Duvenaud
We propose a simple and general variant of the standard reparameterized gradient estimator for the variational evidence lower bound. Specifically, we remove a part of the total der…