Takes a power grid case and generates OPF samples by changing the input parameters.

COnstraint Based Reconstruction and EXascale Analysis (in Julia)

Julia package for the spin wave theory of magnetically ordered quantum spin systems.

This package contains a convenient analysis and visualization pipeline for simple dynamical models of neurons and networks of neurons.

Direct transcription of an optimal control problem and resolution

Standardized regression predictors for use with StatsModels.jl (centered, z-scored, etc.)

Memory efficient seismic inversion via trace estimation

CommonDataModel.jl is a module that defines types common to NetCDF and GRIB data

Chemometrics Data Respository, Scraper, and Fetcher.

Create cohorts from databases utilizing the OMOP CDM

Some helper functions to make some group by operations on DataFrames and IndexedTables faster

Corner Related Algorithms ⛶

Computations on genome locations, inspired by BioConductor.

A Julia interface for cameras

Control for rigid body dynamical systems in maximal coordinates

Utilities of gauge fields

Amaru - Finite element library

Reinforcement learning, compositionally

Useful extensions for Yao

An implementation of the Xi Correlation coefficient and hypothesis test as originally described by Chatterjee (2021).

A set of tools for analyzing molecular dynamics simulations

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Tools for constructing and analyzing the incidence graph or matrix of variables and constraints in a JuMP model

A Julia package for computing SU(N) Clebsch-Gordan Coefficients.

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Network visualization, tensor network, lattice et. al.

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Core algorithms for equation-based modeling

A straightforward interface to the SuiteSparse Matrix Collection

Association Rule Mining in Julia

A package for Julia with several functions to perform satellite analysis.

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A Julia package for Spider Monkey Optimization.

Spherical functions of arbitrary float types

LearningHorse.jl is the ML library for JuliaLang.

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Calculate regressions and abnormal returns for large return datasets quickly

SymPy with PythonCall backend (not PyCall)

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