12 citations · 13 across the 9 of their papers we have counts for
4 papers · 1 filter
Spatio-Temporal Retrieval-based Priors for Adaptive Computational Teaching in Driving
Deepak Edakkattil Gopinath, Xiongyi Cui, Jonathan DeCastro +2
Learning-based automated coaching systems for complex motor tasks such as high-performance driving remain limited in the ability to be adaptive by their reliance only on local, con…
SimCoachCorpus: A naturalistic dataset with language and trajectories for embodied teaching
Emily Sumner, Deepak E. Gopinath, Laporsha Dees +9
High-quality curated datasets are essential for training and evaluating AI approaches, but are often lacking in embodied interactive domains where language and physical action are…
Towards an Autonomous Test Driver: High-Performance Driver Modeling via Reinforcement Learning
John Subosits, Jenna Lee, Shawn Manuel +2
Success in racing requires a unique combination of vehicle setup, understanding of the racetrack, and human expertise. Since building and testing many different vehicle configurati…
Computational Teaching for Driving via Multi-Task Imitation Learning
Deepak Gopinath, Xiongyi Cui, Jonathan DeCastro +10
Learning motor skills for sports or performance driving is often done with professional instruction from expert human teachers, whose availability is limited. Our goal is to enable…