maziarraissi / DeepHPMs
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
☆267Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for DeepHPMs
- Hidden physics models: Machine learning of nonlinear partial differential equations☆141Updated 4 years ago
- ☆232Updated 2 years ago
- ☆171Updated 3 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆322Updated 10 months ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆151Updated last year
- Hidden Fluid Mechanics☆300Updated last year
- ☆114Updated 2 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆251Updated 11 months ago
- ☆276Updated last year
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆137Updated 5 years ago
- ☆366Updated 8 months ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆177Updated 3 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆141Updated last year
- A place to share problems solved with SciANN☆249Updated last year
- PDE-Net: Learning PDEs from Data☆311Updated 3 years ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆308Updated 4 months ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆145Updated 4 years ago
- Physics-informed neural network for solving fluid dynamics problems☆190Updated 3 years ago
- PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks☆289Updated 9 months ago
- Characterizing possible failure modes in physics-informed neural networks.☆119Updated 2 years ago
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆202Updated 2 weeks ago
- Using graph network to solve PDEs☆340Updated last year
- Physics-informed learning of governing equations from scarce data☆112Updated last year
- DeepONet & FNO (with practical extensions)☆220Updated last year
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆157Updated 3 years ago
- ☆152Updated 8 months ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆159Updated 2 years ago
- ☆116Updated 5 years ago
- ☆140Updated 8 months ago
- Physics-informed neural networks package☆260Updated 2 years ago