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cs.LG2023★ 1 cited
On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows
Jia Yu Tee, Oliver De Candido, Wolfgang Utschick +1
Towards safe autonomous driving (AD), we consider the problem of learning models that accurately capture the diversity and tail quantiles of human driver behavior probability distr…
cs.LG2022
Fail-Safe Adversarial Generative Imitation Learning
Philipp Geiger, Christoph-Nikolas Straehle
For flexible yet safe imitation learning (IL), we propose theory and a modular method, with a safety layer that enables a closed-form probability density/gradient of the safe gener…