2.9k citations · 6k across the 15 of their papers we have counts for
10 papers · 1 filter
LOGAN: Latent Optimisation for Generative Adversarial Networks
Yan Wu, Jeff Donahue, David Balduzzi +2
Training generative adversarial networks requires balancing of delicate adversarial dynamics. Even with careful tuning, training may diverge or end up in a bad equilibrium with dro…
Fast Sparse ConvNets
Erich Elsen, Marat Dukhan, Trevor Gale +1
Historically, the pursuit of efficient inference has been one of the driving forces behind research into new deep learning architectures and building blocks. Some recent examples i…
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert +9
Constructing agents with planning capabilities has long been one of the main challenges in the pursuit of artificial intelligence. Tree-based planning methods have enjoyed huge suc…
High Fidelity Speech Synthesis with Adversarial Networks
Mikołaj Bińkowski, Jeff Donahue, Sander Dieleman +5
Generative adversarial networks have seen rapid development in recent years and have led to remarkable improvements in generative modelling of images. However, their application in…
Off-Policy Actor-Critic with Shared Experience Replay
Simon Schmitt, Matteo Hessel, Karen Simonyan
We investigate the combination of actor-critic reinforcement learning algorithms with uniform large-scale experience replay and propose solutions for two challenges: (a) efficient…
Adversarial Video Generation on Complex Datasets
Aidan Clark, Jeff Donahue, Karen Simonyan
Generative models of natural images have progressed towards high fidelity samples by the strong leveraging of scale. We attempt to carry this success to the field of video modeling…