Numerical Methods for Computational Mathematics and Analysis
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Updated
Aug 17, 2024 - Fortran
Numerical Methods for Computational Mathematics and Analysis
Processing of measurement uncertainty of occupational exposure measurements
RascalC: A Fast Code for Galaxy Covariance Matrix Estimation
Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
Pi Approximation written in C++17
Uni{corn|form} toolkit
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.
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
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
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