1.8k citations · 3.8k across the 35 of their papers we have counts for
5 papers · 1 filter
Task-Relevant Adversarial Imitation Learning
Konrad Zolna, Scott Reed, Alexander Novikov +6
We show that a critical vulnerability in adversarial imitation is the tendency of discriminator networks to learn spurious associations between visual features and expert labels. W…
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
Tom Le Paine, Caglar Gulcehre, Bobak Shahriari +11
This paper introduces R2D3, an agent that makes efficient use of demonstrations to solve hard exploration problems in partially observable environments with highly variable initial…
Scaling data-driven robotics with reward sketching and batch reinforcement learning
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov +13
We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned reward functions. We show h…
An Atomistic Machine Learning Package for Surface Science and Catalysis
Martin Hangaard Hansen, José A. Garrido Torres, Paul C. Jennings +4
We present work flows and a software module for machine learning model building in surface science and heterogeneous catalysis. This includes fingerprinting atomic structures from…
Motion Equivariant Networks for Event Cameras with the Temporal Normalization Transform
Alex Zihao Zhu, Ziyun Wang, Kostas Daniilidis
In this work, we propose a novel transformation for events from an event camera that is equivariant to optical flow under convolutions in the 3-D spatiotemporal domain. Events are…