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

WebGL-based 3D visualizer in Julia

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

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

Grid-based simulations in Julia

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

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

Graph Neural Networks in Julia

Abstract types and methods for Gaussian Processes.

A Julia wrapper for libpq

Bayesian Networks for Julia

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.

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

Reservoir computing utilities for scientific machine learning (SciML)

Serving JS to the browser

Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains

Julia wrapper for the ArrayFire library

Abstractions, algorithms, and utilities for reinforcement learning in Julia

Hyperparameter optimization in Julia.

Implementation of normalising flows and constrained random variable transformations

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

Research package for automatic differentiation of programs containing discrete randomness.

A Bayesian Analysis Toolkit in Julia

Solution of nonlinear multiphysics partial differential equation systems using the Voronoi finite volume method

Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC.

Julia wrappers of SymEngine

LowRankModels.jl is a julia package for modeling and fitting generalized low rank models.

Causal inference, graphical models and structure learning in Julia

Computing reachable states of dynamical systems in Julia

This library uses the LaTeX package pgfplots to produce plots.