RascalC: A Fast Code for Galaxy Covariance Matrix Estimation

Uni{corn|form} toolkit

Monte Carlo (MC) Integration and simulations in R and Python

Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX

Pi Approximation written in C++17

A PyTorch implementation of adaptive Monte Carlo Optimal Transport algorithm

A package for multi-dimensional integration using monte carlo methods

Evaluating total cross sections from differential cross sections for 2->n processes, with n>2, can be challenging. This code is intended for solving such problem for massless initial and final state particles and n=3,4 and 5. Furthermore, the framework is kept as simple as possible for this single task.

VegasFlow: accelerating Monte Carlo simulation across multiple hardware platforms

Computing definite integrals using a Monte Carlo method.

Library for multidimensional numerical integration with four independent algorithms: Vegas, Suave, Divonne, and Cuhre.

feyntrop integrates Feynman graphs using tropical sampling

Point inside polygon utilities

Monte Carlo integration is particularly useful when dealing with high-dimensional integrals or integrals over complex, irregularly shaped domains where traditional methods may be impractical. It's widely used in various fields, including physics, finance, and engineering, for solving problems involving numerical integration.

Generate GGX convoluted octahedron mapped textures from cylindrical hdr images.

Physically based renderer based on Nori in C++11

A Quasi-Monte-Carlo Integrator Library with CUDA Support

Machine Learning for Neural Multi-Channel Importance Sampling

CUHK Course code: STAT 3011 | This course is designed to strengthen students' ability in statistical computing as well as in processing and analysing data. Students are required to participate in several term projects with emphasis on techniques of data management and analysis.

An easy way to use multi-GPUs to calculate multi-dimensional integration