I teach the following modules at St Andrews.
CS5010 Artificial Intelligence Principles (2021-now)
Tutorial problem sets on Uncertainty: Probability theory 1, Probability theory 2 , Bayes Net, Approximate Inference
CS5014 Machine Learning (2020-2021)
The following might be interesting to those
keen on taking a (Machine Learning) project with me; and we will probably go through the questions together if needed
who have taken CS5010 AI Principles and want to know more about the underlying maths and statistical learning
who are about to take CS5014 Machine Learning
Maths background
Inference algorithms
I am running a machine learning and data mining reading group within the school. The group is a mixture of faculties and students who share the same interest of learning machine learning and data mining. We meet every two weeks to share reading experience and help each other learn the material. The Github hosting the code and notes for the reading group is here.
In the past we have covered the following topics
Markov Chain Monte Carlo methods: Github link
Variational Inference and Sparsity: Github link
Complex networks
I am currently (co-)supervising: Martin Schiemer (Continual learning), Yingxue Fu (working on computational discourse)
I am also looking for self-motivated students who are interested in Bayesian machine learning, structured dataset mining, statistical inference, Bayesian nonparametrics.