Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

A curated list of awesome Machine Learning frameworks, libraries and software.

Julia Toolkit with fairness metrics and bias mitigation algorithms

COEXI(S)T - Modelling COVID-19 exit strategies for policy makers in the United Kingdom

A Julia machine learning framework

Piecewise Deterministic Sampler library (Bouncy particle sampler, Zig Zag sampler, ...)

Exact Hamiltonian Monte Carlo Sampler for Binary Distributions

MCMC inference in Julia

Copula implementation based on the c++ VineCopulaCPP library of Malte Kurz

Latex macros for linking and organizing mathematical notation