alialaradi / DeepGalerkinMethodLinks
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)
☆117Updated 5 years ago
Alternatives and similar repositories for DeepGalerkinMethod
Users that are interested in DeepGalerkinMethod are comparing it to the libraries listed below
Sorting:
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆154Updated 5 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆57Updated 5 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆176Updated 4 years ago
- hPINN: Physics-informed neural networks with hard constraints☆134Updated 3 years ago
- ☆212Updated 3 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆259Updated last year
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 4 years ago
- ☆41Updated 5 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
- Tutorials on deep learning, Python, and dissipative particle dynamics☆191Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆70Updated 2 years ago
- ☆143Updated 2 years ago
- ☆253Updated 2 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆70Updated 10 months ago
- ☆63Updated 5 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆151Updated 5 months ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆197Updated 2 years ago
- ☆116Updated 5 years ago
- ☆349Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆232Updated 3 years ago
- Physics-informed learning of governing equations from scarce data☆145Updated last year
- Solving PDEs with NNs☆53Updated 2 years ago
- Reproduce the first two numerical experiments(Pytorch)☆26Updated 4 years ago
- ☆166Updated last year
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆92Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆79Updated 3 years ago
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆279Updated 2 years ago
- ☆97Updated 3 years ago