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6 papers · 1 filter
Faithful Inversion of Generative Models for Effective Amortized Inference
Stefan Webb, Adam Golinski, Robert Zinkov +4
Inference amortization methods share information across multiple posterior-inference problems, allowing each to be carried out more efficiently. Generally, they require the inversi…
Non-exchangeable random partition models for microclustering
Giuseppe Di Benedetto, François Caron, Yee Whye Teh
Many popular random partition models, such as the Chinese restaurant process and its two-parameter extension, fall in the class of exchangeable random partitions, and have found wi…
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…
Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes
Hyunjik Kim, Yee Whye Teh
Automating statistical modelling is a challenging problem in artificial intelligence. The Automatic Statistician takes a first step in this direction, by employing a kernel search…
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…