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

MDPs and POMDPs in Julia - An interface for defining, solving, and simulating fully and partially observable Markov decision processes on discrete and continuous spaces.

Probabilistic programming via source rewriting

Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.

"Distributions" that might not add to one.

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

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

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.

System Identification toolbox, compatible with ControlSystems.jl

Beautiful and flexible vizualizations of high dimensional data

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

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

Experimental Julia implementation of the Amazon Braket SDK

WIP successor to Soss.jl

Monte Carlo Tree Search for Markov decision processes using the POMDPs.jl framework

Implementation of the Deep Q-learning algorithm to solve MDPs

A modern OpenGL 4.6 rendering framework, written in Julia.

FMIFlux.jl is a free-to-use software library for the Julia programming language, which offers the ability to place FMUs (fmi-standard.org) everywhere inside of your ML topologies and still keep the resulting model trainable with a standard (or custom) FluxML training process.

The automatically differentiable and GPU-compatible toolkit for CMB analysis.

Online solver based on Monte Carlo tree search for POMDPs with continuous state, action, and observation spaces.

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Simple particle filter implementation in Julia - works with POMDPs.jl models or others.

Julia library for deep reinforcement learning

Integrating diagramming and data visualization

The PO-UCT algorithm (aka POMCP) implemented in Julia

Tools for solving and displaying Keplerian orbits for exoplanets.

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Fast approximate high-dimensional hierarchical Bayesian inference

DSL for probabilistic models specification and probabilistic programming.

Problem models for testing POMDPs.jl

A general branch and bound framework

Octofitter is a Julia package for performing Bayesian inference against direct images of exoplanets, relative astrometry, and astrometric acceleration of the host star.

Concise and friendly interfaces for defining MDP and POMDP models for use with POMDPs.jl solvers

The current implementation of `LinearAlgebra.eigen` does not support sensitivities. DifferentiableEigen.jl offers an `eigen` function that is differentiable by every AD-framework with support for ChainRulesCore.jl or ForwardDiff.jl.

A playground for evolutionary computation in Julia

Random Integrators for many-body quantum systems

Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations

Data and functions to support Julia projects based on the book "Regression and Other Stories" by Andrew Gelman, Jennifer Hill and Aki Vehtari.

Graphical tools for Bayesian inference and posterior predictive checks

Provide all functions needed to work with augmented likelihoods (conditionally conjugate with Gaussians)