#julia

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.

A comprehensive open source computer algebra system for computations in algebra, geometry, and number theory.

Interactive data visualizations and plotting in Julia

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

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

Hydrological modeling

Julia installer and version manager

Data structures in Julia to enable power systems analysis.

The Base interface of the SciML ecosystem

Julia for optimization simulation and modeling of PowerSystems.

Reservoir computing utilities for scientific machine learning (SciML)

Distributed High-Performance Symbolic Regression in Julia

Modular, GPU-capable land surface model of the CliMA Earth System Model, designed for data-driven parameterizations

🎈 Simple reactive notebooks for Julia

Utility package for Sienna's simulation infrastructure

Julia extension for Visual Studio Code

Neural Network primitives with multiple backends

AMD GPU (ROCm) programming in Julia

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

A Julia package for probability distributions and associated functions.

A data structure for mathematical optimization problems

📚 Parameterize, execute, and analyze notebooks

21st century AD

An optimized graphs package for the Julia programming language

🏔️Optimization on Riemannian Manifolds in Julia

Special mathematical functions in Julia

Symbolic expressions, rewriting and simplification