analysiscenter / pydensLinks
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
☆309Updated last year
Alternatives and similar repositories for pydens
Users that are interested in pydens are comparing it to the libraries listed below
Sorting:
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆279Updated 2 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆338Updated last year
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆150Updated 4 months ago
- ☆117Updated 5 years ago
- ☆210Updated 3 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆176Updated 4 years ago
- ☆180Updated 2 months ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆259Updated last year
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆115Updated 3 years ago
- ☆253Updated 2 years ago
- Using graph network to solve PDEs☆392Updated last year
- Automatic Differentiation Library for Computational and Mathematical Engineering☆301Updated last year
- Solving PDEs with NNs☆53Updated 2 years ago
- ☆308Updated last month
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆193Updated 2 years ago
- A place to share problems solved with SciANN☆278Updated last year
- Characterizing possible failure modes in physics-informed neural networks.☆135Updated 3 years ago
- Physics-Informed Neural networks for Advanced modeling☆505Updated this week
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆149Updated 5 years ago
- ☆345Updated 2 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆229Updated 3 years ago
- Code for "Learning data-driven discretizations for partial differential equations"☆168Updated 5 years ago
- OSS library that implements deep learning methods for partial differential equations and much more☆438Updated 3 weeks ago
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆744Updated 3 months ago
- ☆454Updated 2 months ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆417Updated last month
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆117Updated 5 years ago
- Physics Informed Neural Network (PINN) for the wave equation.☆170Updated 4 years ago
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 4 years ago