Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).
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Updated
Aug 22, 2024 - Python
Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).
[ECCV 2024] Reconstruction and Simulation of Elastic Objects with Spring-Mass 3D Gaussians
IsoGCN code for ICLR2021
PENN code for NeurIPS 2022
[NeurIPS 2022] The implementation for the paper "Learning Physical Dynamics with Subequivariant Graph Neural Networks".
An extensible benchmark suite to evaluate data-driven physical simulation
Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).
Code for the paper "Deep learning of thermodynamics-aware reduced-order models from data" published in Computer Methods in Applied Mechanics and Engineering (CMAME).
Applications of the Teg differentiable programming language to problems spanning graphics and physical simulation.
Implementation of CogSci 2019 paper 'Active physical learning via reinforcement learning'
Simulink model and python interface to simulate electrical motor operations.
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