1 citations · 2 across the 3 of their papers we have counts for
3 papers · 1 filter
Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling
Aman Sinha, Payam Nikdel, Supratik Paul +1
Ensuring the safety of autonomous vehicles (AVs) requires both accurate estimation of their performance and efficient discovery of potential failure cases. This paper introduces Ba…
Embedding Synthetic Off-Policy Experience for Autonomous Driving via Zero-Shot Curricula
Eli Bronstein, Sirish Srinivasan, Supratik Paul +4
ML-based motion planning is a promising approach to produce agents that exhibit complex behaviors, and automatically adapt to novel environments. In the context of autonomous drivi…
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving
Eli Bronstein, Mark Palatucci, Dominik Notz +14
We demonstrate the first large-scale application of model-based generative adversarial imitation learning (MGAIL) to the task of dense urban self-driving. We augment standard MGAIL…