analysiscenter / pydens
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
☆303Updated last year
Alternatives and similar repositories for pydens:
Users that are interested in pydens are comparing it to the libraries listed below
- Deep learning for Engineers - Physics Informed Deep Learning☆333Updated last year
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆146Updated last month
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆277Updated 2 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆143Updated 5 years ago
- Solving PDEs with NNs☆50Updated 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
- A place to share problems solved with SciANN☆269Updated last year
- Physics-Informed Neural networks for Advanced modeling☆446Updated this week
- ☆192Updated 3 years ago
- ☆167Updated last year
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆178Updated 2 years ago
- ☆116Updated 5 years ago
- ☆268Updated last week
- ☆320Updated 2 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆256Updated last year
- Characterizing possible failure modes in physics-informed neural networks.☆128Updated 3 years ago
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆220Updated 4 months ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆208Updated 3 years ago
- Using graph network to solve PDEs☆372Updated last year
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆145Updated 5 years ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆359Updated 2 months ago
- Automatic Differentiation Library for Computational and Mathematical Engineering☆295Updated last year
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆176Updated 4 years ago
- ☆428Updated 2 months ago
- ☆409Updated last year
- ☆130Updated 2 years ago
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆728Updated last week
- Physics Informed Neural Network (PINN) for the wave equation.☆149Updated 4 years ago
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆98Updated 9 months ago
- ☆244Updated 2 years ago