Lrs wrapper module for Julia

Train a spiking recurrent neural network

Locality-sensitive hashing (LSH) in Julia.

Typeset scattered graph data rewriter based on LaTeX nodes

A Julia client for the JuliaHub platform

Classical adaptive linear filters in Julia

Wrapper on top of LightGraphs for preserving vertex numbering

Interface designs for enforcing static computations in array functions with Julia

Propagate waves efficiently, optically, physically, differentiably with Julia Lang.

Connecting Julia to the Tax Calculator of the National Bureau of Economic Research (NBER)

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Computation graphs for matrix functions

A library for machine learning datasets on graph

Empirical probability distributions in Julia

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Generate audiory stimuli

Vantage Point Tree in Julia

Tidier analysis of categorical variables, modeled after the forcats R package.

A Julia package for fitting the equation of state of solids, and more

Matching algorithms for LightGraphs.jl

Tools to perform group contribution (GC) identification, given the SMILES of a compound

Implementation of Integral Probability Measures in Julia

A modular hydrodynamic code written in pure Julia

High dimensional numbers and reductions recipes for data visualization of scientific machine learning (SciML)

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A Julia wrapper for the Concorde TSP Solver.

Multivariate cumulants of any order

Finite Element tools in Julia: Analysis of flexible structures, beams and shells

Package Information and Documentation

Transfer entropy (conditional mutual information) estimators for the Julia language

An astrodynamics package for working in the three body problem

Fast and Accurate Computation of Projected Two-point Functions

DSL for Financial Contracts.

Julia dashboard for analysis of cryptocurrency market data

Julia package for finding the longest simple path in a graph.

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Symbolics-based function property propagation for optimization

Experimental features for Flux.jl

A Julia package for Interpretable Compositional Networks (ICN), a variant of neural networks, allowing the user to get interpretable results, unlike regular artificial neural networks.

Local polynomial regression in pure Julia