Publications (4)
Perceptual Gradient Networks
Dmitry Nikulin, Roman Suvorov, Aleksei Ivakhnenko +1
Many applications of deep learning for image generation use perceptual losses for either training or fine-tuning of the generator networks. The use of perceptual loss however incur…
Free-Lunch Saliency via Attention in Atari Agents
Dmitry Nikulin, Anastasia Ianina, Vladimir Aliev +1
We propose a new approach to visualize saliency maps for deep neural network models and apply it to deep reinforcement learning agents trained on Atari environments. Our method add…
Vision-Language Models as a Source of Rewards
Kate Baumli, Satinder Baveja, Feryal Behbahani +24
Building generalist agents that can accomplish many goals in rich open-ended environments is one of the research frontiers for reinforcement learning. A key limiting factor for bui…
TORAX: A Fast and Differentiable Tokamak Transport Simulator in JAX
Jonathan Citrin, Ian Goodfellow, Akhil Raju +11
We present TORAX, a new, open-source, differentiable tokamak core transport simulator implemented in Python using the JAX framework. TORAX solves the coupled equations for ion heat…