A differentiable PDE solving framework for machine learning
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Updated
Feb 28, 2025 - Python
A differentiable PDE solving framework for machine learning
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
A flexible framework for solving PDEs with modern spectral methods.
Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
2D-Finite Element Analysis with Python
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
Deep learning library for solving differential equations on top of PyTorch.
Codomain attention neural operator for single to multi-physics PDE adaptation.
Python script solving the wave equation (équations de D'Alembert) 1D and 2D by taking into account velocity variation.
JAX-DIPS is a differentiable interfacial PDE solver.
PENN code for NeurIPS 2022
Official implementation of Scalable Transformer for PDE surrogate modelling
This repository contains code for the paper "MAgNet: Mesh-Agnostic Neural PDE Solver" https://arxiv.org/abs/2210.05495
Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms
Solving High Dimensional Partial Differential Equations with Deep Neural Networks
A library for building finite difference simulations
Numba-accelerated Pythonic implementation of MPDATA with examples in Python, Julia, Rust and Matlab
A machine learning boosted parallel-in-time differential equation solver framework.
Finite volume toolbox in Python
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