Spotlights

Spotlight Talks

• Watch and Match: Supercharging Imitation with Regularized Optimal Transport
  (Siddhant Haldar, Vaibhav Mathur, Denis Yarats, Lerrel Pinto)

• An Auto-Tuning Framework for Controllers using Auto-Differentiation
  (Sheng Cheng, Minkyung Kim, Lin Song, Zhuohuan Wu, Shenlong Wang, Naira Hovakimyan)

• Train Offline, Test Online: A Real Robot Learning Benchmark
  (Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta)

• Planning Goals for Exploration
  (Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman)

• Leveraging Haptic Feedback to Improve Data Quality and Quantity for Deep Imitation Learning Models
  (Catie Cuan, Allison Okamura, Mohi Khansari)

• Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials
  (Aviral Kumar, Anikait Singh, Frederik Ebert, Yanlai Yang, Chelsea Finn, Sergey Levine)