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 interface.

Julia bindings for the Enzyme automatic differentiator

Interactive data visualizations and plotting in Julia

Update immutable data

Common functional iterator patterns

Symbolic programming for the next generation of numerical software

Symbolic expressions, rewriting and simplification

Calculating contour curves for 2D scalar fields in Julia

Simple, consistent interfaces for any codec.

The Base interface of the SciML ecosystem

Basic interface for manifolds in Julia

Powerful convenience for Julia visualizations and data analysis

Primitives for construction of objects

MPI wrappers for Julia

Filter design, periodograms, window functions, and other digital signal processing functionality

Manifolds.jl provides a library of manifolds aiming for an easy-to-use and fast implementation.

Relax! Flux is the ML library that doesn't make you tensor

AD-backend agnostic system defining custom forward and reverse mode rules. This is the light weight core to allow you to define rules for your functions in your packages, without depending on any particular AD system.

Forward Mode Automatic Differentiation for Julia

Forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs

SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia

Convert julia objects to LaTeX equations, arrays or other environments.

Julia implementation of Data structures

A structure interface for SciML to give queryable properties from user data and parameters

Julia macro for re-exporting one module from another

Julia bindings to the FFTW library for fast Fourier transforms

Julia wrapper for the LLVM C API

Formatted output of timed sections in Julia

Julia functional programming infrastructures and metaprogramming facilities

The base package for Optimization.jl, containing the structs and basic functions for it.

21st century AD

Mathematical functions related to statistics.

Heterogeneous programming in Julia

Abstract julia interfaces for working with trees

A Julia package for defining and working with linear maps, also known as linear transformations or linear operators acting on vectors. The only requirement for a LinearMap is that it can act on a vector (by multiplication) efficiently.

Basic statistics for Julia

A common solve function for scientific machine learning (SciML) and beyond

Repository for automatic differentiation backend types

A Julia package to provide C and Python-like formatting support

Colorschemes, colormaps, gradients, and palettes