58 citations · 86 across the 4 of their papers we have counts for
7 papers
Discretization Drift in Two-Player Games
Mihaela Rosca, Yan Wu, Benoit Dherin +1
Gradient-based methods for two-player games produce rich dynamics that can solve challenging problems, yet can be difficult to stabilize and understand. Part of this complexity ori…
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
Chongli Qin, Yan Wu, Jost Tobias Springenberg +4
The instability of Generative Adversarial Network (GAN) training has frequently been attributed to gradient descent. Consequently, recent methods have aimed to tailor the models an…
Shaping Belief States with Generative Environment Models for RL
Karol Gregor, Danilo Jimenez Rezende, Frederic Besse +3
When agents interact with a complex environment, they must form and maintain beliefs about the relevant aspects of that environment. We propose a way to efficiently train expressiv…
Deep Compressed Sensing
Yan Wu, Mihaela Rosca, Timothy Lillicrap
Compressed sensing (CS) provides an elegant framework for recovering sparse signals from compressed measurements. For example, CS can exploit the structure of natural images and re…
Learning Attractor Dynamics for Generative Memory
Yan Wu, Greg Wayne, Karol Gregor +1
A central challenge faced by memory systems is the robust retrieval of a stored pattern in the presence of interference due to other stored patterns and noise. A theoretically well…
Optimizing Agent Behavior over Long Time Scales by Transporting Value
Chia-Chun Hung, Timothy Lillicrap, Josh Abramson +5
Humans spend a remarkable fraction of waking life engaged in acts of "mental time travel". We dwell on our actions in the past and experience satisfaction or regret. More than mere…