Julia code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Causal Inference using Gaussian Processes with Structured Latent Confounders. Estimate treatment ...
Algorithms for quantifying associations, independence testing and causal inference from data.
Examples for Bayesian inference using DynamicHMC.jl and related packages.
Implementation of a Partial Least Squares Regressor
[draft] Agnostic Machine Learning models working on CPUs, GPUs, distributed architecture, etc.
JuliaLang version of "An Introduction to Statistical Learning: With Applications in R"
A comprehensive QTL analysis tool by multivariate linear mixed model.
A Julia machine learning framework
Computing reachable states of dynamical systems in Julia
Graphical tools for Bayesian inference and posterior predictive checks
Data science and numerical computing with Julia
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/
Book on Julia for Data Science