Geometric loss functions between point clouds, images and volumes

MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.

A Julia package for probability distributions and associated functions.

Optimisers.jl defines many standard optimisers and utilities for learning loops.

Julia bindings for the Enzyme automatic differentiator

Course material for the PhD course in Advanced Bayesian Learning

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

Functions generated at runtime without world-age issues or overhead

A little less conversation, a little more abstraction

JuliaMono is a monospaced font for scientific and technical users, with comprehensive Unicode support.

Tutorial files for the JuliaCon 2020 CxxWrap workshop

Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

Bayesian inference with probabilistic programming.

A great intro dataset for data exploration & visualization (alternative to iris).

Contributor's Guide on Collaborative Practices for Community Packages

Efficient transducers for Julia

Code for the ICML 2019 paper: Distribution Calibration for Regression

Web site of the Computational Optimal Transport book

Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML

My name is Hercule Poirot and I am probably the greatest detective in the world.

Scaled MMD GAN

Example material for "Rewrite It In Rust" presentation

Probabilistic Programming with Gaussian processes in Julia

A Julia package for Gaussian Processes