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3d-quickhull

Header only 3d quickhull in c99

awesome-courses

List of awesome university courses for learning Computer Science!

blazedem

c-parallel-prefix-sum

A C and Pthreads implementation of the prefix sum algorithm

cmake-examples

Useful CMake Examples

convhull_3d

A header-only C implementation of the Quickhull algorithm for building N-dimensional Convex Hulls and Delaunay meshes

cpp-boilerplate

A small c++ template with modern CMake

cuda_by_example

The CMake version of cuda_by_example

data

dem-phasefield

Adaptive phase field modeling of fracture using deep energy minimization.

easy_build

EasyBuild: configure, build and install computational packages with ease

geokeyfem_hm

Qi ZHANG's simulation code

gmshparser

gmshparser is a lightweight, 100 % tested and well documented package that aims to reliably parse the Gmsh ascii file format (.msh). The package does not introduce any external dependencies and thus fits well with the needs of your own FEM research code as a small stand-alone package.

gmshparser-1

A collection of parsers for reading Gmsh mesh-files in format v2 and v4.

graph_dem

graphgalerkin

Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems

icy-2018

ICY: an interface between COMSOL Multiphysics and YADE

meta-contact-search-algorithm

Meta-contact search algorithm implementation in the article “A global direct search method for high-fidelity contact detection between arbitrarily shaped three-dimensional convex polyhedral blocks”

mpm-py

MPM-Py: A program for learning the Material Point Method using Python

neper_dda

transfer neper mesh file to dda file

opengjk-xiwang

Fast and reliable implementation of the Gilbert-Johnson-Keerthi (GJK) algorithm for C, C#, Go, Matlab and Python

particlesystem

CUDA Particle System with OpenGL

percnn-fork

Encoding physics to learn reaction-diffusion processes

pinns-pytorch-examples

PyTorch Implementation of Physics-informed Neural Networks

pinns-pytorch-examples-2

Basic implementation of physics-informed neural network with pytorch.

pinns-tf-raissi-study

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

pinns-tf2.0-examples

TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).

pylith

PyLith is a finite element code for the solution of dynamic and quasi-static tectonic deformation problems.

quickhull

Header-only single-class implementation of Quickhull algorithm for convex hulls finding in arbitrary dimension (>1) space.

resource