61 citations · 156 across the 12 of their papers we have counts for
5 papers · 1 filter
Large-Scale Study of Curiosity-Driven Learning
Yuri Burda, Harri Edwards, Deepak Pathak +3
Reinforcement learning algorithms rely on carefully engineering environment rewards that are extrinsic to the agent. However, annotating each environment with hand-designed, dense…
Compositional GAN: Learning Image-Conditional Binary Composition
Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi +1
Generative Adversarial Networks (GANs) can produce images of remarkable complexity and realism but are generally structured to sample from a single latent source ignoring the expli…
Learning Instance Segmentation by Interaction
Deepak Pathak, Yide Shentu, Dian Chen +4
We present an approach for building an active agent that learns to segment its visual observations into individual objects by interacting with its environment in a completely self-…
Zero-Shot Visual Imitation
Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo +7
The current dominant paradigm for imitation learning relies on strong supervision of expert actions to learn both 'what' and 'how' to imitate. We pursue an alternative paradigm whe…
Investigating Human Priors for Playing Video Games
Rachit Dubey, Pulkit Agrawal, Deepak Pathak +2
What makes humans so good at solving seemingly complex video games? Unlike computers, humans bring in a great deal of prior knowledge about the world, enabling efficient decision m…