33 citations · 51 across the 6 of their papers we have counts for
4 papers · 1 filter
A User's Guide to Calibrating Robotics Simulators
Bhairav Mehta, Ankur Handa, Dieter Fox +1
Simulators are a critical component of modern robotics research. Strategies for both perception and decision making can be studied in simulation first before deployed to real world…
Curriculum in Gradient-Based Meta-Reinforcement Learning
Bhairav Mehta, Tristan Deleu, Sharath Chandra Raparthy +2
Gradient-based meta-learners such as Model-Agnostic Meta-Learning (MAML) have shown strong few-shot performance in supervised and reinforcement learning settings. However, specific…
Generating Automatic Curricula via Self-Supervised Active Domain Randomization
Sharath Chandra Raparthy, Bhairav Mehta, Florian Golemo +1
Goal-directed Reinforcement Learning (RL) traditionally considers an agent interacting with an environment, prescribing a real-valued reward to an agent proportional to the complet…
Active Domain Randomization
Bhairav Mehta, Manfred Diaz, Florian Golemo +2
Domain randomization is a popular technique for improving domain transfer, often used in a zero-shot setting when the target domain is unknown or cannot easily be used for training…