IBM / simulaiLinks
A toolkit with data-driven pipelines for physics-informed machine learning.
☆185Updated last month
Alternatives and similar repositories for simulai
Users that are interested in simulai are comparing it to the libraries listed below
Sorting:
- ☆181Updated 2 months ago
- Physics-Informed Neural networks for Advanced modeling☆515Updated last week
- ☆263Updated 9 months ago
- Characterizing possible failure modes in physics-informed neural networks.☆136Updated 3 years ago
- Using graph network to solve PDEs☆398Updated 3 weeks ago
- OSS library that implements deep learning methods for partial differential equations and much more☆440Updated last month
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆115Updated 3 years ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆144Updated 2 months ago
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆126Updated last year
- ☆116Updated 5 years ago
- A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software☆56Updated last year
- Datasets and code for results presented in the BOON paper☆44Updated 2 years ago
- ☆313Updated 2 months ago
- A library for dimensionality reduction on spatial-temporal PDE☆66Updated last year
- Introductory workshop on PINNs using the harmonic oscillator☆124Updated last month
- Code for paper "Multiple Physics Pretraining for Physical Surrogate Models☆164Updated 6 months ago
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆113Updated 11 months ago
- Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to physics inform model training as well as …☆252Updated 2 weeks ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆151Updated 5 months ago
- Introduction to JAX Workshop @ ETH Zurich, 25 June 2024☆36Updated 2 months ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆177Updated last month
- Codomain attention neural operator for single to multi-physics PDE adaptation.☆59Updated 3 weeks ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆100Updated 10 months ago
- ☆14Updated 9 months ago
- ☆201Updated 11 months ago
- Datasets and code for results presented in the ProbConserv paper☆53Updated last year
- Code for the paper Universal Physics Transformers☆116Updated 4 months ago
- ☆460Updated 2 months ago
- ☆63Updated 3 weeks ago
- ☆62Updated 7 months ago