A Julia package for interpretable machine learning with stochastic Shapley values
MIT License
[draft] Agnostic Machine Learning models working on CPUs, GPUs, distributed architecture, etc.
A solver for nonlinear programming
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
Template for Julia Programming Language packages using the copier engine.
Performance and data profiles
Implementation of a Partial Least Squares Regressor
A benchmarking framework for the Julia language
A shape preserving spline implementation in Julia
Julia implementation of elliptical slice sampling.
Building recommender systems in Julia
Examples for Bayesian inference using DynamicHMC.jl and related packages.
A Julia package for data clustering
A comprehensive QTL analysis tool by multivariate linear mixed model.
Contains a wide-ranging collection of compressed sensing and feature selection algorithms. Exampl...
Slides for the "Interpretable SDM with Julia" workshop