Probabilistic and Unsupervised Learning  Additional material
You'll find here some additional material to help you understand the course. We'll also provide you with the slides used during tutorials. Please note that we will not publish corrections for assignments online.
Additional reading
Please be warned that these are *recommended* reading.
For example, you shouldn't expect the assignments or exams to cover only the chapters in Bishop that we list here. The same is true for any item of this list, you are expected to find additional material about the lecture by yourself when needed.
These are compiled from previous years pages and courses.
Topic  Additional reading 
Statistical Foundations 
 Cribsheet by Iain Murray
 Matrix Identities by Sam Roweis
 Matrix Cookbook by K. Petersen and M. Pedersen
 Tom Minka's notes on matrix algebra
 Bishop: Chapter 1 and 2.
 David MacKay's book: Chapters 13 and 2223. Appendices B, C

Nuances of Probability Theory by Tom Minka.
 Probability Theory: The Logic of Science by ET
Jaynes
 Probability and Statistics Online Reference

Latent Variable Models 
 Bishop: Chapters 3 and 12.
 David MacKay's book: Chapters 2022, 34.
 Max Welling's Class Notes on PCA and FA

EM 
 Bishop: Chapter 9

Time series models 
 Bishop: Chapter 13
 Minka, T. (1999) From Hidden Markov Models to Linear Dynamical Systems
 Welling notes on HMM and Kalman Filter
 Rabiner's tutorial on HMM

Graphical models 
 Bishop: Chapter 8
 MacKay: Chapter 16, 26
 David Heckermann's
Tutorial on Graphical Models

Exact Bayes 
 Bishop: Chapter 6, 4.4, 3.43.5
 MacKay: Chapter 2728, 45
 Carl Rasmussen's
tutorial slides on Gaussian Processes
 A great textbook about Gaussian Processes, available online: Gaussian processes for Machine Learning by Rasmussen and Williams

Expectation Propagation 
 Divergence measures and message passing (Minka 2005)
 Expectation propagation for exponential families (Seeger 2008)
 Graphical models, exponential families and variational inference
(Wainwright, Jordan 2008)
 Notes on EP by Lloyd Elliott.

Tutorials
Here are the slides used during tutorials (when available).
Corrections of assignments will be discussed during the tutorials but not posted here.