Optimization framework for nonlinear, gradient-based constrained, sparse optimization problems.

This library provides arrays with columns padded to be a multiple of SIMD-vector width.

Familiar vectorized routines from R/Python/MATLAB, plus some more.

NuclearToolkit.jl: Julia package for nuclear structure calculations

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Astronomical coordinate systems in Julia

MHLib.jl - A Toolbox for Metaheuristics and Hybrid Optimization Methods in Julia

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A set of tools to quickly generate and visualize autonomous driving scenarios for Algames.jl.

Image inpainting algorithms in Julia

Much faster than BigFloat at precisions up to 3,500 bits (1050 digits)

🌎 Tools for realistic regional-to-global ocean simulations, and coupled ocean + sea-ice simulations based on Oceananigans and ClimaSeaIce. Basis for the ocean and sea-ice component of CliMA's Earth system model.

A version of the STREAM benchmark which measures the sustainable memory bandwidth.

Injecting statistical functions into any SQLite database in Julia

Julia package of regularization functions for machine learning

The weaving paper strips: shape optimization by geometric elasticity

Probability bounds analysis in Julia

Causal Inference with Invariant Prediction

Fixed Point Acceleration for Julia

Powerflow for unbalanced three-phase power distribution systems with distributed generation

Stochastic delay differential equations (SDDE) solvers for the SciML scientific machine learning ecosystem

Specialized tools for MRI

Provide `sound` & `record` functions for playing & recording audio in Julia. Also Julia version of phase vocoder.

Geospatial tables compatible with the GeoStats.jl framework

Motif-based weighted spectral clustering in Python, R and Julia

Differential equation problem specifications and scientific machine learning for common financial models

Naive Bayes classifier

Statistical bootstrap procedures for time-series data

Accelerate your ML research using pre-built Deep Learning Models with Lux

Automates adjoints. Forward and reverse mode algorithmic differentiation around implicit functions (not propagating AD through), as well as custom rules to allow for mixed-mode AD or calling external (non-AD compatible) functions within an AD chain.

Julia package for the plotting of plane curves and surfaces

A Julia/JuMP Package for Maximizing Algebraic Connectivity of Undirected Weighted Graphs

Commonly used test images

Deep Learning made easy and fast

Quasi-Monte-Carlo numerical computation of multivariate normal probabilities

Complex phase portraits for Julia.

Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.

Thin, efficient wrapper around Arb library (http://arblib.org/)

Project Management tools, with a particular focus on PERT charts

Functions for declaring and working with grammars and expression trees in Julia.