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.

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

Middleware for Julia

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

Named dimensions and indexing for julia arrays and other data

Create books with Julia

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

A Julia interface to the NLopt nonlinear-optimization library

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:

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

An intuitive modeling interface for infinite-dimensional optimization problems.

Declarative vector graphics

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

A Julia/JuMP-based Global Optimization Solver for Non-convex Programs

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.

WebGL-based 3D visualizer in Julia

A bridge between Julia and the Web.

Scalable symbolic-numeric set computations in Julia

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

Utility package for accessing common Machine Learning datasets in Julia

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

Fast Estimation of Linear Models with IV and High Dimensional Categorical Variables

Grid-based simulations in Julia

A Julia interface to the SQLite library

A Julia interface to the Gurobi Optimizer

A Julia package for large-scale tensor computations, with a hint of category theory