A longstanding goal of the field of AI is a method for learning a highly capable, generalist
agent from diverse experience. In the subfields of vision and language, this was largely …

Deep reinforcement learning (RL) algorithms are predominantly evaluated by comparing
their relative performance on a large suite of tasks. Most published results on deep RL …

In an effort to overcome limitations of reward-driven feature learning in deep reinforcement
learning (RL) from images, we propose decoupling representation learning from policy …

The ability to separate signal from noise, and reason with clean abstractions, is critical to
intelligence. With this ability, humans can efficiently perform real world tasks without …

Learning effective visual representations that generalize well without human supervision is a
fundamental problem in order to apply Machine Learning to a wide variety of tasks …