Bayesian inference with probabilistic programming.

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

Library for the numerical simulation of closed as well as open quantum systems.

Trixi.jl: Adaptive high-order numerical simulations of conservation laws in Julia

A Julia library for efficient tensor computations and tensor network calculations

Density-functional toolkit

Manifolds.jl provides a library of manifolds aiming for an easy-to-use and fast implementation.

A Julia package to perform Bifurcation Analysis

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

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

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.

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

Package for Simulation, Tomography and Analysis of Quantum Computers

Interior point solver for general convex conic optimization problems

Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

System Identification toolbox, compatible with ControlSystems.jl

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.

MIRT: Michigan Image Reconstruction Toolbox (Julia version)

MagNav: airborne Magnetic anomaly Navigation

Core functions for the Julia (2nd) edition of the text Fundamentals of Numerical Computation, by Driscoll and Braun.

A framework for simulating viscous incompressible flows about arbitrary body shapes.

Macros and functions to work with DSGE models.

Nonlinear eigenvalue problems in Julia: Iterative methods and benchmarks

Pure Julia Implementation of Geometrically Exact Beam Theory

A Julia rewrite of Dynare: solving, simulating and estimating DSGE models.

Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)

Solution of Lyapunov, Sylvester and Riccati matrix equations using Julia

High level functions for analyzing the output of simulations

Preheat your MCMC

Clique recycling non-Gaussian (multi-modal) factor graph solver; also see Caesar.jl.

Bayesian Generalized Linear models using `@formula` syntax.

A simple tool for simulating trapped ion systems

Simulation of quantum systems on a lattice

Turing + Makie = Turkie

Building dynamical systems compositionally