research
∙
09/15/2023
Compositional Foundation Models for Hierarchical Planning
To make effective decisions in novel environments with long-horizon goal...
share
research
∙
07/24/2023
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation
Reinforcement learning is time-consuming for complex tasks due to the ne...
research
∙
02/27/2023
Statistical Learning under Heterogenous Distribution Shift
This paper studies the prediction of a target 𝐳 from a pair of random va...
research
∙
11/28/2022
Is Conditional Generative Modeling all you need for Decision-Making?
Recent improvements in conditional generative modeling have made it poss...
research
∙
10/06/2022
Distributionally Adaptive Meta Reinforcement Learning
Meta-reinforcement learning algorithms provide a data-driven way to acqu...
research
∙
07/05/2022
Offline RL Policies Should be Trained to be Adaptive
Offline RL algorithms must account for the fact that the dataset they ar...
research
∙
10/26/2020
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning
Reinforcement learning (RL) has achieved impressive performance in a var...
research
∙
09/08/2020
Long-Horizon Prediction and Uncertainty Propagation with Residual Point Contact Learners
The ability to simulate and predict the outcome of contacts is paramount...
research
∙
04/13/2019
Combining Physical Simulators and Object-Based Networks for Control
Physics engines play an important role in robot planning and control; ho...
research
∙
08/09/2018