75 citations · 169 across the 6 of their papers we have counts for
10 papers
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects
Anthony Simeonov, Yilun Du, Beomjoon Kim +4
We present a framework for solving long-horizon planning problems involving manipulation of rigid objects that operates directly from a point-cloud observation, i.e. without prior…
AdaScale SGD: A User-Friendly Algorithm for Distributed Training
Tyler B. Johnson, Pulkit Agrawal, Haijie Gu +1
When using large-batch training to speed up stochastic gradient descent, learning rates must adapt to new batch sizes in order to maximize speed-ups and preserve model quality. Re-…
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
Richard Li, Allan Jabri, Trevor Darrell +1
Learning robotic manipulation tasks using reinforcement learning with sparse rewards is currently impractical due to the outrageous data requirements. Many practical tasks require…
Superposition of many models into one
Brian Cheung, Alex Terekhov, Yubei Chen +2
We present a method for storing multiple models within a single set of parameters. Models can coexist in superposition and still be retrieved individually. In experiments with neur…
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…