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.

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

Named dimensions and indexing for julia arrays and other data

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

Julia bindings to Vega-Lite

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

[DEPRECATED] Bioinformatics and Computational Biology Infrastructure for Julia

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

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

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

A toolbox for satellite analysis written in julia language.

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.

Fast jacobian computation through sparsity exploitation and matrix coloring

WebGL-based 3D visualizer in Julia

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

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

Grid-based simulations in Julia

Graph Neural Networks in Julia

A Julia wrapper for libpq

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.

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.

Julia package registration bot

Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner

Raster manipulation for the Julia language

Julia wrapper for the ArrayFire library

Serving JS to the browser

Abstractions, algorithms, and utilities for reinforcement learning in Julia

Performant arrays where each dimension can have a named axis with values