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

Scalable symbolic-numeric set computations in Julia

Julia bindings for the Enzyme automatic differentiator

Update immutable data

DuckDB is an analytical in-process SQL database management system

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

Calculating contour curves for 2D scalar fields in Julia

Print data in formatted tables.

LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.

Simple, consistent interfaces for any codec.

The Base interface of the SciML ecosystem

Julia client for MLFlow.

Powerful convenience for Julia visualizations and data analysis

Primitives for construction of objects

CUDA programming in Julia.

HDF5-compatible file format in pure Julia

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

An interface to various automatic differentiation backends in Julia.

In-memory tabular data in Julia

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

Julia macro for re-exporting one module from another

Julia wrapper for the LLVM C API

Formatted output of timed sections in Julia

Julia functional programming infrastructures and metaprogramming facilities

Compile your Julia Package

Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.

21st century AD

Direct solution of large sparse systems of linear algebraic equations in pure Julia

Mathematical functions related to statistics.

Heterogeneous programming in Julia

A Julia machine learning framework

Basic statistics for Julia

A data structure for mathematical optimization problems

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