PDE-Net: Learning PDEs from Data
☆331Jun 26, 2021Updated 4 years ago
Alternatives and similar repositories for PDE-Net
Users that are interested in PDE-Net are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- A pyTorch Extension for Applied Mathematics☆41Mar 17, 2020Updated 6 years ago
- ☆280Nov 4, 2022Updated 3 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆34Oct 30, 2023Updated 2 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆96May 11, 2022Updated 4 years ago
- Numerical Experiments☆15Jan 21, 2018Updated 8 years ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Code for "Learning data-driven discretizations for partial differential equations"☆167Aug 19, 2025Updated 9 months ago
- ☆26Jun 16, 2018Updated 7 years ago
- ☆196May 10, 2021Updated 5 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆366Dec 20, 2023Updated 2 years ago
- source code of learning to discretize solving 1d scalar conservation laws via deep reinforcement learning☆15Feb 2, 2021Updated 5 years ago
- Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch☆15Sep 13, 2021Updated 4 years ago
- Deep Learning application to the partial differential equations☆30May 5, 2018Updated 8 years ago
- Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators☆818Jun 25, 2022Updated 3 years ago
- Using graph network to solve PDEs☆448Jun 2, 2025Updated last year
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- Learning in infinite dimension with neural operators.☆3,682May 11, 2026Updated last month
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆291Jul 30, 2022Updated 3 years ago
- ☆17May 21, 2020Updated 6 years ago
- Deep BSDE solver in TensorFlow☆295Apr 18, 2025Updated last year
- ☆50Nov 6, 2023Updated 2 years ago
- Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations☆5,917Feb 11, 2026Updated 4 months ago
- Deep Galerkin Method☆17Feb 10, 2019Updated 7 years ago
- Paper List For Linking ODE and Deep Learning☆244Feb 18, 2020Updated 6 years ago
- ☆15May 11, 2020Updated 6 years ago
- Open source password manager - Proton Pass • AdSecurely store, share, and autofill your credentials with Proton Pass, the end-to-end encrypted password manager trusted by millions.
- A library for scientific machine learning and physics-informed learning☆4,223Mar 1, 2026Updated 3 months ago
- Towards Physics-informed Deep Learning for Turbulent Flow Prediction☆28Oct 18, 2021Updated 4 years ago
- ☆18Jul 27, 2018Updated 7 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Jan 24, 2021Updated 5 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆45Jan 13, 2019Updated 7 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Mar 25, 2023Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆170Jul 19, 2023Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆98Aug 17, 2023Updated 2 years ago
- A differentiable PDE solving framework for machine learning☆1,883Updated this week
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond☆1,894Oct 10, 2025Updated 8 months ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆159Feb 20, 2020Updated 6 years ago
- Sparse Physics-based and Interpretable Neural Networks☆53Sep 30, 2021Updated 4 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Mar 20, 2023Updated 3 years ago
- UNIVR PDE course project and just for fun☆118May 26, 2017Updated 9 years ago
- ☆10Sep 21, 2019Updated 6 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆6,442Apr 4, 2025Updated last year