Dependency aware feature selection

Dyadic kernel density estimation in Julia

Differential Inequality Algorithms for Parametric ODEs

Empirical Bayes shrinkage in Julia

Networks. Boil 'em mash 'em stick 'em in a stew. And now, plot 'em.

Effect size measures

A package for embeddings processing

Plotting functionality for Agents.jl - Agent-Based Modelling in Julia

This Package comprises a collection of ensemble algorithms for prediction, in order to improve the predictive performance for classification and regression problems.

Code generation for Euler-Lagrange equations.

A Julia package for probability distributions member of the Exponential family

Manifolds for the natural parameters of members of the exponential family of distributions

High Level API Finite Element Methods based on ExtendableGrids and ExtendableFEMBase

Guaranteed parallel root finding focused on speed and reliability

Deep and convolutional neural networks with feedback operations in Flux.

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Particle filtering using the Feynman-Kac formalism

FishTank.jl creates an e-fish for you in case you feel lonely when you are coding.

A JuMP extension for conducting flexibility analysis.

A Julia package containing GNC algorithms for autonomous aerospace systems

A comprehensive QTL analysis tool by multivariate linear mixed model.

A unification of (hyper)graph model generation.

Models of gas-phase atmospheric chemistry and related processes

Implement the Kasahara-Shimotsu Test to decide number of components in Gaussian Mixture Model.

Tools to pick data in an interactive manner

Geostatistical learning solvers for the GeoStats.jl framework

Geostatistical functions for the GeoStats.jl framework

Geospatial transforms for the GeoStats.jl framework

Integrate deep neural network and reverse mode automatic differentiation into Gauss process, have fun !

GraviPet is the General Relativistic Astrophysics Visualization, Initialization, and Postprocessing Efficient Toolkit

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Simulation engine for Heta-based models

Atmospheric aNd Instrument models in the Measurement Equation

Implicitly defined graphs (possibly infinite)

Generate nice reports from MCMC-based approximations

Infinite random arrays in Julia.

Conduct one-way and multi-way anova in Julia with GLM.jl

Distributions and Sampleables with keys for the variates

Implement different KL Divergences analytically or by sampling

Lathe is an inclusive Predictive Learning module for Julia