Course Outline
Lecture 1 (notes:slides)
Bayes' Theorem and Bayesian Inference
Lecture 2 (notes:slides)
Bayesian Decision Trees
Lecture 3 (notes:slides)
Evidence and message passing
Lecture 4 (notes:slides)
Inference in singly connected networks
Lecture 5 (notes:slides)
Building networks from data
Lecture 6 (notes:slides)
Cause and Independence
Lecture 7 (notes:slides)
Model Accuracy
Lecture 8 (notes:slides)
Approximate Inference
Lecture 9 (notes:slides)
Exact Inference
Lecture 10 (notes:slides)
Probability propagation in Join Treess
Lecture 11 (slides)
Graphical Models
Lecture Slides on Gaussian Processes
Lecture Slides on Bayesian Optimisation
Coursework:
Data Files for the coursework
Errata
Past Exam Papers:
Note that for the topics covered in lectures 11-17 the exam questions may be different
in style from earlier years.
2005 ,
2006 ,
2007 ,
2008 ,
2009 ,
2010
2011 ,
2012 ,
2013 ,
2014 ,
2015 ,
2016
2017