Building Assistive Sensorimotor Interfaces through Human-in-the-Loop Machine Learning
Siddharth Reddy [2022]
Large-Scale Real-World Robotic Manipulation Using Diverse Data
Frederik Ebert [2022]
Scalable Robot Learning
Ashvin Nair [2022]
Towards Adaptive, Continual Embodied Agents
Kelvin Xu [2022]
Acquiring Motor Skills Through Motion Imitation and Reinforcement Learning
Xue Bin Peng [2021]
Adaptation Based Approaches to Distribution Shift Problems
Marvin Zhang [2021]
Building Reinforcement Learning Algorithms that Generalize: From Latent Dynamics Models to Meta-Learning
JD Co-Reyes [2021]
Goal-Directed Exploration and Skill Reuse
Vitchyr Pong [2021]
How to Train Your Robot: Techniques for Enabling Robotic Learning in the Real World
Abhishek Gupta [2021]
Infrastructure Support for Datacenter Applications
Michael Chang [2021]
Offline Learning for Scalable Decision Making
Justin Fu [2021]
Real World Robot Learning: Learned Rewards, Offline Datasets and Skill Re-Use
Avi Singh [2021]
Compositionality and Modularity for Robot Learning
Coline Devin [2020]
Learning and Analyzing Representations for Meta-Learning and Control
Kate Rakelly [2020]
Mobile Robot Learning
Gregory Kahn [2020]
Model-based Deep Reinforcement Learning for Robotic Systems
Anusha Nagabandi [2020]
Visual Dynamics Models for Robotic Planning and Control
Alex Lee [2019]
Acquiring Diverse Robot Skills via Maximum Entropy Deep Reinforcement Learning
Tuomas Haarnoja [2018]
Learning to Learn with Gradients
Chelsea Finn [2018]