1k citations · 5.3k across the 132 of their papers we have counts for
3 papers · 2 filters
Distral: Robust Multitask Reinforcement Learning
Yee Whye Teh, Victor Bapst, Wojciech Marian Czarnecki +5
Most deep reinforcement learning algorithms are data inefficient in complex and rich environments, limiting their applicability to many scenarios. One direction for improving data…
Filtering Variational Objectives
Chris J. Maddison, Dieterich Lawson, George Tucker +5
When used as a surrogate objective for maximum likelihood estimation in latent variable models, the evidence lower bound (ELBO) produces state-of-the-art results. Inspired by this,…
Particle Value Functions
Chris J. Maddison, Dieterich Lawson, George Tucker +4
The policy gradients of the expected return objective can react slowly to rare rewards. Yet, in some cases agents may wish to emphasize the low or high returns regardless of their…