90 citations · 185 across the 7 of their papers we have counts for
4 papers · 1 filter
Grasp2Vec: Learning Object Representations from Self-Supervised Grasping
Eric Jang, Coline Devin, Vincent Vanhoucke +1
Well structured visual representations can make robot learning faster and can improve generalization. In this paper, we study how we can acquire effective object-centric representa…
WAIC, but Why? Generative Ensembles for Robust Anomaly Detection
Hyunsun Choi, Eric Jang, Alexander A. Alemi
Machine learning models encounter Out-of-Distribution (OoD) errors when the data seen at test time are generated from a different stochastic generator than the one used to generate…
QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor +8
In this paper, we study the problem of learning vision-based dynamic manipulation skills using a scalable reinforcement learning approach. We study this problem in the context of g…
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods
Deirdre Quillen, Eric Jang, Ofir Nachum +3
In this paper, we explore deep reinforcement learning algorithms for vision-based robotic grasping. Model-free deep reinforcement learning (RL) has been successfully applied to a r…