A Julia package to perform Bifurcation Analysis

A JuMP extension for Stochastic Dual Dynamic Programming

XGBoost Julia Package

Julia implementation of various rigid body dynamics and kinematics algorithms

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

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

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 interface to SymPy via PyCall

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:

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.

WebGL-based 3D visualizer in Julia

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

Scalable symbolic-numeric set computations in Julia

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

A Julia wrapper for libpq

Bayesian Networks for Julia

Abstract types and methods for Gaussian Processes.

Financial market technical analysis & indicators in Julia

Algorithms inspired by graph Laplacians: linear equation solvers, sparsification, clustering, optimization, etc.

Tidier data visualization in Julia, modeled after the ggplot2 R package.

A library of data interpolation and smoothing functions

Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications

Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.