Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

Powerful convenience for Julia visualizations and data analysis

21st century AD

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

Symbolic programming for the next generation of numerical software

Optimization functions for Julia

A Julia package for probability distributions and associated functions.

Forward Mode Automatic Differentiation for Julia

Statically sized arrays for Julia

Macro(s) for vectorizing loops.

Progress meter for long-running computations

Julia implementation of Data structures

Formatted output of timed sections in Julia

HTTP for Julia

A benchmarking framework for the Julia language

Physical quantities with arbitrary units

Basic statistics for Julia

An opinionated code formatter for Julia. Plot twist - the opinion is your own.

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

Symbolic expressions, rewriting and simplification

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

Fast, continuous interpolation of discrete datasets in Julia

Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration.

An optimized graphs package for the Julia programming language

Julia bindings for the Enzyme automatic differentiator

Statistical plotting recipes for Plots.jl

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

A Julia package for evaluating distances (metrics) between vectors.

Types with default field values, keyword constructors and (un-)pack macros

High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.

Julia functional programming infrastructures and metaprogramming facilities

A data structure for mathematical optimization problems

A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)

Overdub Your Julia Code

Heterogeneous programming in Julia

Plotting for Julia based on GR, a framework for visualisation applications

A Julia package for data clustering

Special mathematical functions in Julia

Reverse Mode Automatic Differentiation for Julia

Root finding functions for Julia