Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
☆63Jan 25, 2022Updated 4 years ago
Alternatives and similar repositories for graphGalerkin
Users that are interested in graphGalerkin are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Nov 3, 2021Updated 4 years ago
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆79Apr 17, 2026Updated 3 months ago
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 2 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Jan 24, 2021Updated 5 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆169May 15, 2024Updated 2 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆82Feb 1, 2023Updated 3 years ago
- Physics-informed neural networks with hard constraints for inverse design☆162Nov 21, 2021Updated 4 years ago
- An automatic knowledge embedding framework for scientific machine learning☆23May 15, 2022Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆52Mar 24, 2022Updated 4 years ago
- Standard Material Point Method 2D code for beginners☆14Aug 7, 2021Updated 4 years ago
- Discovering Conservation Laws using Optimal Transport and Manifold Learning☆22Sep 23, 2023Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Jul 23, 2020Updated 6 years ago
- PENN code for NeurIPS 2022☆42Jan 11, 2023Updated 3 years ago
- ☆11Oct 15, 2025Updated 9 months ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆57May 30, 2023Updated 3 years ago
- ☆426Dec 3, 2022Updated 3 years ago
- Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)☆16Feb 17, 2021Updated 5 years ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆111Aug 22, 2024Updated last year
- A deep energy method (DEM) to solve J2 elastoplasticity problems in 3D.☆29Jan 20, 2023Updated 3 years ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆18Jan 9, 2024Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆99Aug 17, 2023Updated 2 years ago
- Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control☆58May 16, 2022Updated 4 years ago
- This repository offers a collection of simulation datasets from mechanical simulations of metamaterials. Jupyter notbooks demonstrate how…☆18Nov 1, 2022Updated 3 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Differentiable Physics-informed Graph Networks☆67Feb 20, 2020Updated 6 years ago
- Enhancing the convergence speed by 2x and improving the training success of Physics-Informed Neural Networks (PINNs).☆13Oct 14, 2024Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆96Aug 26, 2025Updated 11 months ago
- Physics Informed Sparse Identification of Nonlinear Dynamics☆13Jan 3, 2025Updated last year
- This is the implementation of the PI-UNet for HSL-TFP☆29Feb 19, 2023Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆170Jul 19, 2023Updated 3 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆112Apr 15, 2022Updated 4 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆34Mar 19, 2026Updated 4 months ago
- 【清华大学《计算机动画原理与算法》大作业】MPM fluid simulation and surface reconstruction using Taichi; A path tracer implemented by LuisaCompute python front…☆14Jan 16, 2024Updated 2 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- ☆11Jun 22, 2026Updated last month
- The code is for two phase demonstration as example 1 shown in the paper - Gao, Yi, and Yongming Liu. "Reliability-based topology optimiza…☆12Dec 27, 2021Updated 4 years ago
- An open-source AMR CFD solver specializing in compressible reacting flows☆15Oct 8, 2025Updated 9 months ago
- A Python package for modeling linear viscoelasticity with fractional rheology models☆24Feb 3, 2026Updated 5 months ago
- A MLS-MPM based 3D fluid system simulation implemented with Taichi☆25Feb 6, 2024Updated 2 years ago
- Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh …☆10Dec 2, 2022Updated 3 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆298Oct 12, 2021Updated 4 years ago