Macros and functions to work with DSGE models.

Automatic dualization feature for MathOptInterface.jl

Optimal transport algorithms for Julia

A Julia library of summation-by-parts (SBP) operators used in finite difference, Fourier pseudospectral, continuous Galerkin, and discontinuous Galerkin methods to get provably stable semidiscretizations, paying special attention to boundary conditions.

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

Julia interface to SCIP solver

A helper tool for visualizing and editing a ModelingToolkit.jl system connections

Semidefinite programming optimization solver

A Julia package for numerical computation in quantum information theory

Timeseries in Julia

Julia implementation for various Frank-Wolfe and Conditional Gradient variants

Beta Machine Learning Toolkit

Bayesian optimization for Julia

Algorithms that combine tensor network methods with automatic differentiation

A Julia package for estimating ARMA-GARCH models.

Pure Julia implementations of single-pass object detection neural networks.

A fully `Distributions.jl`-compliant copula package

Optimization Problems for Julia

Dive deeper into your data with interactive graphics

Pure Julia Implementation of Geometrically Exact Beam Theory

Package implementing common state-space routines.

Build flexible hierarchical multi-instance learning models.

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

Rigorous floating-point calculations with interval arithmetic in Julia

CliMA model dycore

Projective geometry for computer vision in Julia

Stochastic Optimization, Learning, Uncertainty and Sampling

FMI.jl is a free-to-use software library for the Julia programming language which integrates FMI (fmi-standard.org): load or create, parameterize, differentiate and simulate FMUs seamlessly inside the Julia programming language!

Julia Library for Interatomic Potentials

Writing financial contracts 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.

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

A Julia interface to the Coin-OR Branch and Cut solver (CBC)

A Julia interface for the SCS conic programming solver

Implements Optimization and approximate uncertainty quantification algorithms, Ensemble Kalman Inversion, and Ensemble Kalman Processes.

Spin dynamics and generalization to SU(N) coherent states

Solve Fractional Differential Equations using high performance numerical methods

High level functions for analyzing the output of simulations