YoungForever222

JavaGuide

「Java学习+面试指南」一份涵盖大部分 Java 程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

grok-1

Grok open release

taichi

Productive, portable, and performant GPU programming in Python.

ml-agents

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

ardupilot

ArduPlane, ArduCopter, ArduRover, ArduSub source

tutorials

PyTorch tutorials.

machine-learning-yearning-cn

Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著

PINNs

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

FluidX3D

The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL. Free for non-commercial use.

trfl

TensorFlow Reinforcement Learning

Deep-Reinforcement-Learning-Hands-On

Hands-on Deep Reinforcement Learning, published by Packt

deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

SU2

SU2: An Open-Source Suite for Multiphysics Simulation and Design

jax-cfd

Computational Fluid Dynamics in JAX

chebfun

Chebfun: numerical computing with functions.

CoupleGenerator

Generate your lover with your photo

realworldrl_suite

Real-World RL Benchmark Suite

gym-rocketlander

A SpaceX Rocket Lander environment for OpenAI gym using Box2D

HFM

Hidden Fluid Mechanics

PDE-FIND

Cylinder2DFlowControlDRL

code for performing active flow control of the 2D Karman street using Deep Reinforcement Learning

smarties

Lightweight and scalable framework for Reinforcement Learning

Grokking-Deep-Learning-with-Julia

DeepCGP

Deep convolutional gaussian processes.

openLBMPM

openLBMPM is an open source lattice Boltzmann method (LBM) package for multicomponent and multiphase (MCMP) flow and transport in porous media. Currently, it includes Shan-Chen method and color gradient method for MCMP system. There are two options for Shan-Chen method: (1) Original Shan-Chen method, which integrates the force term to the equilibrium velocity and cannot reach high viscosity ratio; (2) Explicit forcing model developed by M.Porter et al (2012). For color gradient model, the methods developed by Liu et.al (2014), Huang et al (2014) and Takashi et al (2018) are included. For running the codes, CUDA and numba (from Anaconda) are required

caption-eval

Sentence/Caption evaluation using automated metrics

FLUSI

Fluid-Structure-Interaction / MHD Research Code. Relies on Fourier transforms for derivatives and the volume penalization method to include obstacles.

lifev

LifeV parallel finite element library

lifev-env-patches

Import via Terminal & Euler

trfl

TensorFlow Reinforcement Learning