aliakhav

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

jupyter-book

Create beautiful, publication-quality books and documents from computational content.

ml-road

Machine Learning Resources, Practice and Research

deepxde

A library for scientific machine learning and physics-informed learning

pysindy

A package for the sparse identification of nonlinear dynamical systems from data

ParaView

VTK-based Data Analysis and Visualization Application

prettytensor

Pretty Tensor: Fluent Networks in TensorFlow

cookbook-2nd-code

Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]

scipy-cookbook

Scipy Cookbook

latex-beamerposter

The LaTeX beamerposter package

dmtcp

DMTCP: Distributed MultiThreaded CheckPointing

spectralDNS

Spectral Navier Stokes (and similar) solvers in Python

adflow

ADflow is a finite volume RANS solver tailored for gradient-based aerodynamic design optimization.

lbann

Livermore Big Artificial Neural Network Toolkit

pythonMCMC

A list of Python-based MCMC & ABC packages

pyJHTDB

Python wrapper for the Johns Hopkins turbulence database library

turbulence-modeling-PIML

Data-driven Reynolds stress modeling with physics-informed machine learning

UQTk

Sandia Uncertainty Quantification Toolkit

bcnn

3D Bayesian Convolutional Neural Network (BCNN) for Credible Geometric Uncertainty. Code for the paper: https://arxiv.org/abs/1910.10793

Oasis

pytricubic

Tricubic interpolation module for Python.

LSTM_ROM_Arxiv

A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks. arXiv:1804.09269

tbnn

This code implements the Tensor Basis Neural Network (TBNN) as described in Ling et al. (Journal of Fluid Mechanics, 2016).

hercules

HERCULES: An open-source, massively parallel direct numerical simulation solver

gmls-nets

PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential operators, PDEs, and other features.

Turb_ML_Papers

A collection of relevant literature related to advancement of machine learning techniques for turbulence modeling and analysis

HIT_MPI

Parallel version of HIT

machine-learning-turbulence

Py4Incompact3D

Python library for postprocessing data produced using Incompact3d