Gerardo Duran-Martin

prml. Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

weighted-likelihood-filter. Code for the paper "Outlier-robust Kalman Filtering through Generalised Bayes" presented at ICML 2024

bayes. Neat Bayesian machine learning examples

reinforcement-learning. Repository of notes, code and notebooks in Python for the book "Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto

martingale-posterior-neural-networks. Martingale posterior neural networks for fast sequential decision making @ Neurips 2025

BONE. Repository for the paper "BONE: a unifying framework for Bayesian online learning in non-stationary environments"

rebayes-mini. Minimalist version of probml/rebayes

misc. Collection of code without a particular purpose.

deep-learning-bishop. Notes and code from the book Deep Learning: Foundations and Concepts by C. Bishop and H. Bishop

filtering-notes. Jupyter Notebook

prediction-learning-games. Notebook and scripts of Prediction, Learning, and Games by Nicolò Cesa-Bianchi

QMUL. Repository of code and notes for the MSc. in Maths at Queen Mary University of London

gerdm.nabla.mx. Personal Blog

simple-jax. Recipes for machine learning using Jax (as simple as possible)

machine_learning. A repository with a bunch of machine learning

pknn.jl. Probabilistic k-nearest neighbours

TGMAFFIRO. Theoretical Grounds and Market Adaptations of Financial FX and Interest Rate Options

analysis-ml. Jupyter Notebook

online-learning-talk. Slides for the online-learning-talk from a Bayesian perspective.

elements-smc. Jupyter Notebook

hard-em-lvm. Jupyter Notebook

aistats2022. Subspace EKF neural bandit presentation for AIStats 2022

rl-ou-process. Reinforcement Learning over an Ornstein Uhlenbeck process

convex_nonconvex. A personal essay about convexity problems in machine learning

ISLR. Exercises, code and analyses of the Introduction to Statistical Learning book and MOOC