A library for scientific machine learning and physics-informed learning
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Updated
May 23, 2024 - Python
A library for scientific machine learning and physics-informed learning
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]
The SciML Scientific Machine Learning Software Organization Website
physics-informed neural network for elastodynamics problem
Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)
Generative Pre-Trained Physics-Informed Neural Networks Implementation
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems
Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
A C++ library for physics-informed spatial and functional data analysis over complex domains.
A repository for the discussion of PDE tooling for scientific machine learning (SciML) and physics-informed machine learning
Using TensorFlow for physics-informed neural networks for scientific machine learning (SciML)
Smart Tensors Tutorials
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software
Accompanying code for "Weak form generalized Hamiltonian learning"
study code for physics informed machine learning and deep learning
Physics-informed deep super-resolution of spatiotemporal data
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