Kolmogorov Arnold Networks

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Surrogate Modeling Toolbox

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

Reinforcement Learning examples implementation and explanation

Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities

A Python library for Secure and Explainable Machine Learning

More than twenty practical cases with real datasets of application of Machine Learning to the field of Cybersecurity

JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework

Robust ML in Astro

Dynamic causal Bayesian optimisation

ML/Stats based predictions to UEFA Euro 2024

Transformer-guided diffusion for galaxy clustering. Code repository associated with https://arxiv.org/abs/2311.17141

Simulator for the UEFA Champions League group stage draw.

Code used in "Dynamics-Informed Gaussian Process models in Stone Soup" paper