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.

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.

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

Graph Neural Networks in Julia

Bayesian Networks for Julia

Abstract types and methods for Gaussian Processes.

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

Sensible extensions for exposing torch in Julia.

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

Raster manipulation for the Julia language

Reservoir computing utilities for scientific machine learning (SciML)

Abstractions, algorithms, and utilities for reinforcement learning in Julia

Hyperparameter optimization in Julia.

Implementation of normalising flows and constrained random variable transformations

Research package for automatic differentiation of programs containing discrete randomness.

A Bayesian Analysis Toolkit in Julia

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

BlockArrays for Julia

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

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

Tools for the exploration of chaos and nonlinear dynamics

Robust robotic localization and mapping, together with NavAbility(TM). Reach out to info@wherewhen.ai for help.

A Julia package for solving systems of polynomials via homotopy continuation.

A package for binary and continuous, single and multi-material, truss and continuum, 2D and 3D topology optimization on unstructured meshes using automatic differentiation in Julia.

Kernel density estimators for Julia

Boosted trees in Julia

Fast, general-purpose interactive applications for complex systems

Julia hybrid constraint programming solver enhanced by a reinforcement learning driven search.

An interface to various automatic differentiation backends in Julia.

Implementations of the models from the Statistical Rethinking book with Turing.jl

Causal, Higher-Order, Probabilistic Programming

Core functionality for the MLJ machine learning framework

Sparse tensors in Julia and more! Datastructure-driven array programing language.

Automatic Finite Difference PDE solving with Julia SciML

Implementation of domain-specific language (DSL) for dynamic probabilistic programming

A Julia package for statistical inference, data manipulation and visualization of phylogenetic networks