XGBoost Julia Package

Julia implementation of various rigid body dynamics and kinematics algorithms

Automatic Differentiation Library for Computational and Mathematical Engineering

Linear operators for discretizations of differential equations and scientific machine learning (SciML)

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

COSMO: Accelerated ADMM-based solver for convex conic optimisation problems (LP, QP, SOCP, SDP, ExpCP, PowCP). Automatic chordal decomposition of sparse semidefinite programs.

A Curious Cumulation of CUDA Cuisine

Julia for optimization simulation and modeling of PowerSystems. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Krylov methods for linear problems, eigenvalues, singular values and matrix functions

AMD GPU (ROCm) programming in Julia

Named dimensions and indexing for julia arrays and other data

StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.

Create books with Julia

Julia bindings to the FFTW library for fast Fourier transforms

Julia interface to SymPy via PyCall

Julia bindings to Vega-Lite

GenX: a configurable power system capacity expansion model for studying low-carbon energy futures. More details at : https://genx.mit.edu

Types and utility functions for summarizing Markov chain Monte Carlo simulations

Types and utility functions for summarizing Markov chain Monte Carlo simulations

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

Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.

[DEPRECATED] Bioinformatics and Computational Biology Infrastructure for Julia

Julia package for automated Bayesian inference on a factor graph with reactive message passing

:rocket: Julia package for orthogonal polynomial transforms :snowboarder:

High-performance metaheuristics for optimization coded purely in Julia.

Markov chain Monte Carlo (MCMC) for Bayesian analysis in julia

An intuitive modeling interface for infinite-dimensional optimization problems.

The JuliaFEM software library is a framework that allows for the distributed processing of large Finite Element Models across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

A differential eDSL that can run faster than light and go back to the past.

A toolbox for satellite analysis written in julia language.

Declarative vector graphics

Specifying, fitting, and evaluating statistical models in Julia

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

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.

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.

Fast jacobian computation through sparsity exploitation and matrix coloring

WebGL-based 3D visualizer in Julia

Mathematical functions related to statistics.

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

A bridge between Julia and the Web.