Summer School
Bayesian Inference
Foundations and Applications

17 to 27 January 2018
Updating…  As yet, this website contains only the most important elements necessary for immediate purposes. Further pages and content are being added incrementally.

Bayesian Inference

Bayesian Inference has in the last two decades emerged from the shadow world of specialist arcana to occupy a central role in scientific inquiry. On the one hand, its interpretation of probability has clearly philosophical aspects while attracting its share of criticism for uncritical use.

With rising computing power and Monte Carlo techniques, the demanding tasks implied by Bayesian analysis have become increasingly feasible even on the desktop, and both general and specialist packages are now available.

It has undoubtedly opened up entire fields to quantitative analysis. The google scholar search for the word Bayesian yields 2.1 million results and reveals the breadth and scope of the fields to which it is being applied. Interest has been further heightened with the advent of buzzwords like machine learning and of artificial intelligence which both contain a significant portion of Bayesian thinking and techniques and connections to causality, probabilistic graphical models, networks and many more.

The need for well-founded understanding and relevant schooling is therefore self-evident. On the one hand, many researchers and students would benefit from the tools provided; on the other hand, the inherent assumptions and limitations should also be understood.


This 2018 School is part of the series of Chris Engelbrecht Summer Schools in Theoretical Physics. While the series has over the years focused mainly on physics topics, the wide applicability of Bayesian inference should make it attractive to students and scientists from many fields. The focus remains on STEM (Science, Technology, Engineering and Mathematics) and the lectures will be pitched accordingly, but anyone from academia or business is welcome.

The 2018 School is aimed both at established researchers and postgraduate students. Depending on time available, research presentations and interactive research group hacks will be set up during the last days of the school. The course component will offer both an introductory course and advanced topics. We have an excellent group of lecturers confirmed for participation.

The venue is located in Bettys Bay adjacent to the Harold Porter National Botanical Garden and bordering on the World Heritage Kogelberg Nature Reserve.

Two separate schools in Bayesian analysis have previously been held in Stellenbosch in 2013 and 2016.

At least 20 sponsorships are available for postgraduate students resident in South Africa; more may become available later.

There is an open email list server to which interested parties can subscribe to receive announcements and messages.

Organising Committee

  1. Hans Eggers (Stellenbosch University, Dept of Physics, Chair)
  2. Michiel de Kock (Stellenbosch University, Dept of Physics)
  3. Yabebal Fantaye (African Institute for Mathematical Sciences)
  4. Steve Kroon (Stellenbosch University, Dept of Computer Science)
  5. Hugo Touchette (SA National Institute for Theoretical Physics)


This School is sponsored by the National Institute for Theoretical Physics.