AI4Equations / dueLinks
A Deep Learning Library for Modeling Unknown Equations
☆25Updated 2 weeks ago
Alternatives and similar repositories for due
Users that are interested in due are comparing it to the libraries listed below
Sorting:
- Repository for the course Numerical Methods for Partial Differential Equations at ETH Zurich.☆38Updated last week
- ☆50Updated 2 years ago
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆77Updated last month
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆181Updated 4 years ago
- ☆70Updated last year
- Tutorials on deep learning, Python, and dissipative particle dynamics☆202Updated 3 years ago
- A Python package for spectral proper orthogonal decomposition (SPOD).☆114Updated 3 weeks ago
- Immersed Boundary Projection Method☆118Updated 5 years ago
- ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…☆129Updated 2 weeks ago
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆20Updated 3 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆147Updated 5 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆25Updated last year
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆57Updated 11 months ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆86Updated 3 months ago
- ☆113Updated last year
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- ☆63Updated 6 years ago
- MATLAB codes for physics-informed dynamic mode decomposition (piDMD)☆161Updated last year
- Supporting codes for the numerical implementations in the paper "Operator inference for non-intrusive model reduction with quadratic mani…☆11Updated 3 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- Implementation of the Deep Ritz method and the Deep Galerkin method☆61Updated 5 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆40Updated 5 months ago
- Easy Reduced Basis method☆92Updated this week
- Code for "Deep Nitsche Method: Deep Ritz Method with Essential Boundary Conditions"☆16Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Multi-fidelity reduced-order surrogate modeling☆28Updated 6 months ago
- Deep Learning for Reduced Order Modelling☆102Updated 4 years ago
- ☆53Updated last year
- The VECMA toolkit for creating surrogate models of multiscale systems.☆20Updated 11 months ago
- ☆273Updated 3 years ago