Numerical Methods
Showing 31 of 31 projects
Matlab implementation of machine learning algorithms from Bishop's Pattern Recognition and Machine Learning textbook.
A high-performance TensorFlow library for quantitative finance, providing mathematical methods, pricing models, and calibration tools.
A simple C++ geometry processing library for manipulating and analyzing 3D meshes.
A comprehensive linear algebra library for Rust with support for statically-sized and dynamically-sized matrices.
A comprehensive Go scientific library for numerical simulations, linear algebra, differential equations, and computational geometry.
A C# library for 2D/3D geometric computing, mesh algorithms, and spatial data structures, compatible with Unity.
An efficient C++ library for robotics, optimal control, and model predictive control with a focus on online performance.
A collection of reusable scientific computing software components for solving large-scale, complex multi-physics engineering problems.
A framework for building parallel, multi-disciplinary simulation software, focusing on modularity, extensibility, and high-performance computing.
A Python library for parallel active learning of mathematical functions, intelligently sampling parameter spaces to minimize evaluations.
A JavaScript library for linear least-squares curve fitting and regression analysis.
A comprehensive statistical computation library for Rust, providing distributions, functions, and utilities for scientific computing.
A Python module that adds a native quaternion dtype to NumPy for efficient 3D rotation and orientation calculations.
A Python library for triangular mesh smoothing and optimization with multiple algorithms and a simple interface.
A pure Python library for finite element assembly, transforming bilinear forms into sparse matrices and linear forms into vectors.
A JAX library for nonlinear optimization including root finding, minimization, fixed points, and least squares.
A Python framework for gradient-free optimization, featuring common algorithms like genetic algorithms and simulated annealing.
A C++ header-only library of statistical distribution functions with compile-time computing capabilities.
A V library for AI and high-performance scientific computing with pure-V BLAS/LAPACK implementations.
A V library for AI and high-performance scientific computing with pure-V BLAS/LAPACK implementations.
An interactive book about Riemann problems and approximate solvers for hyperbolic PDEs, implemented in Jupyter notebooks.
Python code for teaching computational economics, implementing Solow, Ramsey, and Real Business Cycle models.
A high-level environment for solving integral and differential equations in many dimensions using adaptive, fast methods with guaranteed precision.
A Rust binding for the GNU Scientific Library (GSL), providing access to numerical routines for scientific computing.
A Python library providing orthogonal polynomial classes for lines, triangles, disks, spheres, n-cubes, and nD spaces with stable recurrence schemes.
A high-performance unified C++ framework implementing domain decomposition methods for solving large-scale elliptic PDEs on parallel computers.
Statistical functions and distributions for Elixir, including descriptive statistics and probability distributions.
A Python library for fast computation of geometric properties in simplex meshes (triangles, tetrahedra, n-simplices) of any dimension.
A Python library for computing accurate sums and dot products, mitigating floating-point errors in numerical computations.
Integer and fixed-point square root functions using only addition, subtraction, and bit shifts.
A scientific library for the D programming language providing numerical routines and LAPACK bindings.
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