End-to-End Differentiable Physics for Learning and Control

Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen, Josh Tenenbaum, J. Zico Kolter

Nov-20-2025, 17:54:03 GMT–Neural Information Processing Systems

We present a differentiable physics engine that can be integrated as a module in deep neural networks for end-to-end learning.

artificial intelligence, machine learning, reinforcement learning, (17 more...)

Neural Information Processing Systems

Nov-20-2025, 17:54:03 GMT

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    - Reinforcement Learning (0.95)
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