NVIDIA / physicsnemo-symLinks
Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to physics inform model training as well as higher level abstraction for domain experts
☆258Updated last month
Alternatives and similar repositories for physicsnemo-sym
Users that are interested in physicsnemo-sym are comparing it to the libraries listed below
Sorting:
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆201Updated 2 years ago
- Applications of PINOs☆129Updated 2 years ago
- Geometry-Aware Fourier Neural Operator (Geo-FNO)☆265Updated last month
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆432Updated 2 weeks ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆145Updated 3 months ago
- ☆470Updated 3 months ago
- ☆317Updated 2 months ago
- Deep learning for Engineers - Physics Informed Deep Learning☆343Updated last year
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆233Updated 8 months ago
- ☆111Updated 5 months ago
- Physics Informed Neural Network (PINN) for the wave equation.☆179Updated 5 years ago
- A place to share problems solved with SciANN☆283Updated last year
- ☆214Updated 3 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆236Updated 3 years ago
- Physics-Informed Neural networks for Advanced modeling☆529Updated last week
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆181Updated 2 months ago
- Using graph network to solve PDEs☆399Updated last month
- ☆190Updated 2 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆153Updated 6 months ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆149Updated 5 years ago
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆242Updated 2 months ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆180Updated 2 years ago
- DeepONet & FNO (with practical extensions)☆312Updated 2 years ago
- This repository containts materials for End-to-End AI for Science☆175Updated last month
- Characterizing possible failure modes in physics-informed neural networks.☆137Updated 3 years ago
- A large-scale benchmark for machine learning methods in fluid dynamics☆207Updated 7 months ago
- Example problems in Physics informed neural network in JAX☆80Updated last year
- Differentiable Fluid Dynamics Package☆429Updated last month
- ☆138Updated 8 months ago
- ☆354Updated 2 years ago