Autonomous Driving at NeurIPS 2020

Co-organizing the NeurIPS Workshop on Machine Learning for Autonomous Driving

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Publications

Out-of-training-distribution (OOD) scenarios are a common challenge of learning agents at deployment, typically leading to arbitrary …

We study how representation learning can accelerate reinforcement learning from rich observations, such as images, without relying …

Transporting suspended payloads is challenging for autonomous aerial vehicles because the payload can cause significant and …

Forecasting the motion of multiple interacting vehicles. When one is autonmous, conditioning on its goals helps better-predict the …

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