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

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.

Multivariate polynomials interface

Symbolic expressions, rewriting and simplification

High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.

DiffEq solvers for ordinary differential equations

Project Preferences Package

A Differentiation Without A Difference

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 a…

The slow descent into madness

The Julia Language: A fresh approach to technical computing.

Collection of builder repositories for BinaryBuilder.jl

DiffEq related functionality for defining biological models

A bunch of functions which are helpful for maintaining large Github organizations

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem

A common interface for quadrature and numerical integration for the SciML scientific machine learning organization

DiffEq solvers for stochastic differential equations

Differential equation problem specifications and scientific machine learning for common financial models

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

The Base interface of the SciML ecosystem

Symbolic-Numeric Neural DAEs and Universal Differential Equations for Automating Scientific Machine Learning (SciML)

A library of data interpolation and smoothing functions

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

Fast and differentiable implementations of matrix exponentials, Krylov exponential matrix-vector multiplications ("expmv"), KIOPS, ExpoKit functions, and more. All your exponential needs in SciML f…

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.

A thin wrapper over Bridge.jl for the SciML scientific machine learning common interface, enabling new methods for neural stochastic differential equations (neural SDEs)

Interface to DASKR, a differential algebraic system solver for the SciML scientific machine learning ecosystem

Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF) in the SciML scientific machine learning organization