Publications
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GPT-4 Technical Report
OpenAI
arXiv, 2023
[paper] -
Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth
Filipe de Avila Belbute-Peres, J. Zico Kolter
ICLR 2023
[paper] -
HyperPINN: Learning parameterized differential equations with physics-informed hypernetworks
Filipe de Avila Belbute-Peres, Yifan Chen, Fei Sha
Symbiosis of Deep Learning and Differential Equations Workshop, NeurIPS 2021 (Spotlight)
[paper] -
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] -
Assessing the similarity of cortical object and scene representations through cross-validated voxel encoding models
Nicholas M Blauch, Filipe de Avila Belbute-Peres, Juhi Farooqui, Alireza Chaman Zar, David Plaut, Marlene Behrmann
Journal of Vision
[poster] [link] -
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 (Spotlight)
[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]