Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Award winning software library for nonlinear dynamics and nonlinear timeseries analysis

Julia Animations and Visualizations

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

An extensible framework for geospatial data science and geostatistical modeling fully written in Julia

Statistical plotting recipes for Plots.jl

GenX: a configurable power system capacity expansion model for studying low-carbon energy futures. More details at : https://genx.mit.edu

A Bayesian Analysis Toolkit in Julia

This library uses the LaTeX package pgfplots to produce plots.

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

Differentiable RayTracing in Julia

Convenience meta-package to load essential packages for statistics

Gaussian Process package based on data augmentation, sparsity and natural gradients

Perceptually Uniform Colour Maps for Julia

Koma is a Pulseq-compatible framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in pulse sequence development.

MADS: Model Analysis & Decision Support

Large scale Gaussian Mixture Models

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

Hidden Markov Models for Julia.

Dive deeper into your data with interactive graphics

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

Projective geometry for computer vision in Julia

OrbitalTrajectories.jl is a modern orbital trajectory design, optimisation, and analysis library for Julia, providing methods and tools for designing spacecraft orbits and transfers via high-performance simulations of astrodynamical models.

Julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets.

Julia implementation of unsupervised learning methods for time series datasets. It provides functionality for clustering and aggregating, detecting motifs, and quantifying similarity between time series datasets.

Simulated Method of Moments for Julia

Solid state detector field and charge drift simulation in Julia

Julia package for formulating and analyzing stochastic recourse models.

The amazing Reaction Mechanism Simulator for simulating large chemical kinetic mechanisms

Dithering algorithms in Julia.

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

A foolproof way of doing ML with GUI elements.

Spectral clustering algorithms written in Julia

Neuroimaging in Julia

Partitioning images into meaningful regions

Population Genetics in Julia

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Image feature detection for the Julia language

Solve the travelling salesman problem using a mixed integer optimization algorithm with JuMP

Julia library for deep reinforcement learning