  Generalised Bayesian learning algorithms are increasingly popular in machine
learning, due to their PAC generalisation properties and flexibility. The
present paper aims at providing a self-contained survey on the resulting
PAC-Bayes framework and some of its main theoretical and algorithmic
developments.
