#
physics-informed-learning
Here are
26 public repositories
matching this topic...
A library for scientific machine learning and physics-informed learning
Updated
Dec 5, 2022
Python
Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Updated
Dec 5, 2022
Julia
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
Updated
Dec 5, 2022
Julia
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Updated
Mar 1, 2022
Python
physics-informed neural network for elastodynamics problem
Updated
Jan 20, 2022
Python
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)
Updated
Dec 1, 2022
Julia
Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]
Updated
Oct 12, 2021
Python
The SciML Scientific Machine Learning Software Organization Website
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
A repository for the discussion of PDE tooling for scientific machine learning (SciML) and physics-informed machine learning
Updated
Nov 21, 2019
Jupyter Notebook
Using TensorFlow for physics-informed neural networks for scientific machine learning (SciML)
Updated
Nov 30, 2020
Julia
Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
Updated
Dec 24, 2021
Python
Physics-informed deep super-resolution of spatiotemporal data
Updated
Aug 3, 2022
Python
Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
Updated
Dec 2, 2022
Python
A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software
Weak For Generalized Hamiltonian Learning
Updated
Feb 13, 2021
Jupyter Notebook
Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning
Updated
Nov 30, 2022
HTML
Updated
May 25, 2022
Python
Updated
Nov 3, 2022
Jupyter Notebook
Nonnegative Tensor Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning
Updated
Aug 23, 2022
Julia
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