alialaradi / DeepGalerkinMethod
Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, D. Naiff, G. Jardim and Y. Saporito (https://arxiv.org/abs/1811.08782)
☆116Updated 5 years ago
Alternatives and similar repositories for DeepGalerkinMethod:
Users that are interested in DeepGalerkinMethod are comparing it to the libraries listed below
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆150Updated 5 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆55Updated 4 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆175Updated 4 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 years ago
- ☆199Updated 3 years ago
- hPINN: Physics-informed neural networks with hard constraints☆130Updated 3 years ago
- Group project for Deep Learning: Algorithms and Applications in Peking University 2018 Spring. This is a brief survey, discussion and imp…☆44Updated 6 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 4 years ago
- ☆250Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆69Updated 2 years ago
- ☆41Updated 4 years ago
- Tutorials on deep learning, Python, and dissipative particle dynamics☆185Updated 2 years ago
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆279Updated 2 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆258Updated last year
- Solving PDEs with NNs☆53Updated 2 years ago
- Python codes for Introduction to Computational Stochastic PDE☆42Updated 2 months ago
- ☆62Updated 5 years ago
- ☆92Updated 3 years ago
- ☆160Updated last year
- ☆132Updated 2 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆114Updated 3 years ago
- ☆116Updated 5 years ago
- Automatic Differentiation Library for Computational and Mathematical Engineering☆301Updated last year
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆220Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆140Updated last year
- ☆333Updated 2 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆77Updated 2 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆67Updated 4 years ago
- Basic implementation of physics-informed neural networks for solving differential equations☆84Updated 3 months ago