The Julia Programming Language

Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)

Package to call Python functions from the Julia language

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable i…

Black-box optimization for Julia

A data structure for mathematical optimization problems

Root finding functions for Julia

Taylor polynomial expansions in one and several independent variables.

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

🚀 Julia package for orthogonal polynomial transforms 🏂

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

A Julia package for large-scale tensor computations, with a hint of category theory

Implementation of normalising flows and constrained random variable transformations

Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox

A Julia library of summation-by-parts (SBP) operators used in finite difference, Fourier pseudospectral, continuous Galerkin, and discontinuous Galerkin methods to get provably stable semidiscretiz…

illustrates using Julia and MPI to do Monte Carlo