325 citations · 435 across the 7 of their papers we have counts for
7 papers
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…
Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems
Aman Sinha, Matthew O'Kelly, Russ Tedrake +1
Learning-based methodologies increasingly find applications in safety-critical domains like autonomous driving and medical robotics. Due to the rare nature of dangerous events, rea…
FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis
Aman Sinha, Matthew O'Kelly, Hongrui Zheng +3
Balancing performance and safety is crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conse…
Efficient Black-box Assessment of Autonomous Vehicle Safety
Justin Norden, Matthew O'Kelly, Aman Sinha
While autonomous vehicle (AV) technology has shown substantial progress, we still lack tools for rigorous and scalable testing. Real-world testing, the evaluati…
In-silico Risk Analysis of Personalized Artificial Pancreas Controllers via Rare-event Simulation
Matthew O'Kelly, Aman Sinha, Justin Norden +1
Modern treatments for Type 1 diabetes (T1D) use devices known as artificial pancreata (APs), which combine an insulin pump with a continuous glucose monitor (CGM) operating in a cl…
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
Matthew O'Kelly, Aman Sinha, Hongseok Namkoong +2
While recent developments in autonomous vehicle (AV) technology highlight substantial progress, we lack tools for rigorous and scalable testing. Real-world testing, the $\textit{de…