maziarraissi / DeepHPMsLinks
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
☆279Updated 2 years ago
Alternatives and similar repositories for DeepHPMs
Users that are interested in DeepHPMs are comparing it to the libraries listed below
Sorting:
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- ☆253Updated 2 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆193Updated 2 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆338Updated last year
- ☆210Updated 3 years ago
- ☆117Updated 5 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆149Updated 5 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆259Updated last year
- ☆345Updated 2 years ago
- Hidden Fluid Mechanics☆327Updated 2 years ago
- ☆141Updated 2 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆150Updated 4 months ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆229Updated 3 years ago
- PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks☆309Updated last year
- Characterizing possible failure modes in physics-informed neural networks.☆135Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆144Updated last year
- ☆454Updated 2 months ago
- A place to share problems solved with SciANN☆278Updated last year
- PDE-Net: Learning PDEs from Data☆315Updated 3 years ago
- ☆97Updated 3 years ago
- ☆63Updated 5 years ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆153Updated 5 years ago
- ☆180Updated 2 months ago
- hPINN: Physics-informed neural networks with hard constraints☆133Updated 3 years ago
- DeepONet & FNO (with practical extensions)☆300Updated last year
- ☆165Updated last year
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆146Updated 4 years ago
- Physics-informed neural networks package☆308Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆78Updated 2 years ago
- ☆308Updated last month