Coloring algorithms for sparse Jacobian and Hessian matrices

The Base interface of the SciML ecosystem

An interface to various automatic differentiation backends in 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 i…

An implementation of the VPMR algorithm, approximating decaying kernels by sum of exponentials.

Public development project of the LAMMPS MD software package

Implementation of a robust, performant language-level autograd compiler for Julia

Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms

DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia

Base functionality library for QuantumOptics.jl

Common quantum objects, isomophisms, and indexing used across the Piccolo.jl ecosystem

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

Library for the numerical simulation of closed as well as open quantum systems.

CUDA programming in Julia.

A Photonic Quantum Computer Simulator written in Python and C++.

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

SparseArrays.jl is a Julia stdlib

Preheat your MCMC

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…

Boundary value problem (BVP) solvers for scientific machine learning (SciML)

A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools

Fast operator-overloading Jacobian & Hessian sparsity detection.

Arrays with arbitrarily nested named components.

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