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

RascalC: A Fast Code for Galaxy Covariance Matrix Estimation

Implemented two numerical integration techniques in MATLAB: Monte Carlo Integration and Gauss-Legendre Quadrature.

A new Python wrapper for the Cuba library

My PRs: https://github.com/users/Ramy-Badr-Ahmed/projects/7

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

Master Lab: Conditional Resampled Importance Sampling and ReSTIR

Monte Carlo Method (MCM) for incorporating measurement uncertainty in the frequentist analysis of occupational exposure by inhalation to chemical agents

Uni{corn|form} toolkit

Pi Approximation written in C++17

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

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.

Bases MC integrator

VegasFlow: accelerating Monte Carlo simulation across multiple hardware platforms

Computing definite integrals using a Monte Carlo method.

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.