A Theory of Weak-Supervision and Zero-Shot Learning

Victims of Algorithmic Violence: An Introduction to AI Ethics and Human-AI Interaction

The practicalities of academic research ethics - how to get things done

Statistics, ethical and unethical: Some historical vignettes

Joining Bayesian submodels with Markov melding

Neural Networks and Deep Kernel Shaping

Introduction to Advanced Research Computing at Oxford

Ethics from the perspective of an applied statistician

A Day in the Life of a Statistics Consultant

Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte-Carlo

Modelling infectious diseases: what can branching processes tell us?

Causality and Autoencoders in the Light of Drug Repurposing for COVID-19

Recent Applications of Stein's Method in Machine Learning

Do Simpler Models Exist and How Can We Find Them?

Practical pre-asymptotic diagnostic of Monte Carlo estimates in Bayesian inference and machine learning

Complexity of local MCMC methods for high-dimensional model selection

Assessing Personalization in Digital Health

Machine Learning in Drug Discovery

Several structured thresholding bandit problems

A primer on PAC-Bayesian learning *followed by* News from the PAC-Bayes frontline