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9eqmodel_knfandlstm

academic-kickstart

causalpinns

cfdpython-es

Una serie de IPython notebooks traducidos de "12 Steps to Navier-Stokes" http://lorenabarba.com/

course-content

deephpms

Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations

deepxde

deepxde-1

A library for scientific machine learning and physics-informed learning

dlforcompmath

A repository of jupyter hub tutorials for the PIMS CRG Summer School: "Deep Learning for Computational Mathematics."

drlinfluids

An open-source Python platform of coupling deep reinforcement learning and OpenFOAM

fsiwithfreefem

gpytorch

A highly efficient implementation of Gaussian Processes in PyTorch

ibm_capstone_project

ihpcss2022

Material for the MPI and OpenMP hands-on session at IHPCSS2022

ihpcss_dl_workshop

IHPCSS DL Workshop

ihpcss_programming_challenge_2022

learning-python-physics-informed-machine-learning-pinns-deeponets

Physics Informed Machine Learning Tutorials (Pytorch and Jax)

m2pi.ca

machine-learning-applied-to-cfd

Examples of how to use machine learning algorithms in computational fluid dynamics.

ml-cfd-lecture

Lecture material for machine learning applied to computational fluid mechanics

mmctools

Collection of preprocessing, postprocessing, and analysis code for mesoscale-to-microscale coupling (MMC)

myfoam

Additional OpenFOAM solvers for compressible flows

myturbulencemodels

Additional turbulence models for OpenFOAM

openfoam-9

OpenFOAM Foundation repository for OpenFOAM version 9

openfoam-dev

OpenFOAM Foundation development repository

physics-informed-neural-network-in-jax

Example problems in Physics informed neural network in JAX

pinn

Physics-Informed Neural Network

pinnpapers

Must-read Papers on Physics-Informed Neural Networks.

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

pinns-1

PINNs is a python library for physics-informed machine learning.