539 citations · 1.5k across the 37 of their papers we have counts for
5 papers · 1 filter
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning
Yecheng Jason Ma, Andrew Shen, Osbert Bastani +1
Reinforcement Learning (RL) agents in the real world must satisfy safety constraints in addition to maximizing a reward objective. Model-based RL algorithms hold promise for reduci…
Probabilistic Modeling for Human Mesh Recovery
Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman +1
This paper focuses on the problem of 3D human reconstruction from 2D evidence. Although this is an inherently ambiguous problem, the majority of recent works avoid the uncertainty…
Conservative Offline Distributional Reinforcement Learning
Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani
Many reinforcement learning (RL) problems in practice are offline, learning purely from observational data. A key challenge is how to ensure the learned policy is safe, which requi…
Keyframe-Focused Visual Imitation Learning
Chuan Wen, Jierui Lin, Jianing Qian +2
Imitation learning trains control policies by mimicking pre-recorded expert demonstrations. In partially observable settings, imitation policies must rely on observation histories,…
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
Jingxi Xu, Bruce Lee, Nikolai Matni +1
The difficulty of optimal control problems has classically been characterized in terms of system properties such as minimum eigenvalues of controllability/observability gramians. W…