Simulate a fisheries creel survey.

An ensemble of machine learning models for detecting fraudulent credit card transactions, utilizing advanced techniques for feature selection, data imbalance handling, and hyperparameter tuning.

Uni{corn|form} toolkit

BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.

Parametric Voronoi generator with real time editing and SVG export

A class-leading water system implemented in Unity

A R package to perform uniform sampling in the environmental space

Sampling methods for data streams

Microsynthesis using quasirandom sampling and/or IPF

Methods for optimizing the spatial location of biodiversity-observation-networks

An open-source JAX-based statistical sampling toolkit 🧪

Coding ML models, Sampling Methods, Feature Selection algorithms from scratch

Design of experiments for Python

Python library for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

MCMC sample analysis, kernel densities, plotting, and GUI

Improved sampling via learned diffusions (ICLR2024) and an optimal control perspective on diffusion-based generative modeling (TMLR2024)

Repository to the notes and relevant codes from previous lectures and talks.

Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.

A Python library for efficient feature ranking and selection on sparse data sets.

Implementation of a coupled Metropolis-Hasting Algorithm in Jax. Project done as part of the Bayesian Machine Learning course by Rémi Bardenet and Julyan Arbel.