Research

  • Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
    Filipe de Avila Belbute-Peres, Thomas D. Economon, J. Zico Kolter
    ICML 2020
      [paper]   [code]

  • End-to-End Differentiable Physics for Learning and Control
    Filipe de Avila Belbute-Peres, Kevin Smith, Kelsey Allen, Josh Tenenbaum, J. Zico Kolter
    NeurIPS 2018
    [paper]   [code]

  • A Modular Differentiable Rigid Body Physics Engine
    Filipe de Avila Belbute-Peres, J. Zico Kolter
    Deep Reinforcement Learning Symposium, NIPS 2017
    [paper]   [code]

  • Thinking inside the box: Motion prediction in contained spaces uses simulation
    Kevin A. Smith, Filipe de Avila Belbute-Peres, Edward Vul, Joshua B. Tenenbaum
    CogSci 2017
    [paper]   [poster]