The Cambridge Ellis Unit Summer School on Probabilistic Machine Learning is from 17-21 July 2023 at the Department of Computer Science and Technology

The Cambridge Ellis Unit Summer School on Probabilistic Machine Learning is a distinguished course offered to graduate students, researchers and professionals, featuring engaging experts in their respective field and/or world-recognized professionals speaking about advanced machine learning concepts.

Important Dates

Application deadline: 15 May 2023

Admission notification by: 5 June 2023


  • Statistical Emulation
  • Uncertainty Quantification
  • Evaluation of Probablistic Models
  • Re-inforcement Learning
  • Application RL
  • Inference/PN
  • Application BO
  • Introduction to Diffusion Models
  • Normalising Flows
  • Deep Generative Models
  • Application of Diffusion Models
  • Variational Inference and Stein Discrepancy
  • Probablistic Models in Computer Vision and Graphics
  • Machine Learning and the Physical World

Lecturers (Confirmed)

Neill Campbell
David Ginsbourger
José Miguel Hernández Lobato
Katja Hofmann
Yingzhen Li
Maren Mahsereci
Carl Rasmussen
Tony O'Hagan
Ian Osband
Arno Solin
Mike Tipping
Rich Turner
Mark van der Wilk
Francisco Vargas
Tian Xie


Please see the proposed schedule below.

Items followed by * are arranged by the organisers but need to paid for separately.

Dates17 July 202318 July 202319 July 202320 July 202321 July 2023
ThemesIntroduction to Probablistic ModelingProbabilistic Models/Sequential Decision Making Probabilistic NumericsImplicit Models/Diffusion ModelsFurther Probabilistic Modeling
09:00Carl RasmussenMark van der WilkNico KramerFrancisco VargasRich Turner
10:30BreakBreakBreakBreakYingzhen Li
11:00Mike TippingIan OsbanJonathan WengerJosé Miguel Hernández Lobato
12:30LunchLunchPoster session
13:00Tian XieNeill Campbell
13:30 Tony O'HaganKatja Hoffman
14:30BreakMaren MahserecMarc DeisenrothNeil Lawrence
15:00David GinsbourgerBreak
15:30Arno SolinPoster Session
Farewell Reception
17:15Science Tour- 90 min*
19:00-22:00Evening Dinner at Sidney Sussex College*
19:30Cambridge Shakespeare Festival-
Much Ado About Nothing *

The Summer School will be in person and held at the Department of Computer Science and Technology.

You can see travel information here.

This is an inperson event but we will record talks when we can and put on our Youtube channel.


All attendees will need to cover their own accommodation and travel costs. 

Travel awards are available for attendees from under-represented backgrounds. Those selected to attend will then be given a chance to apply for the travel grant. Please email for more information.

There are no fees to attend the Summer School.

Lunch and tea/coffee will be provided.


Those wishing to attend the Cambridge Ellis Machine Learning Summer School will need to complete this form.

You will also have to supply:

  • 2 page CV
  • Letter of Reference: The writer should assess the qualities, characteristics, and capabilities of the person being recommended in terms of that individual’s abilities. The letter should address the applicant’s background and potential in Machine Learning, academic standing compared to other students, and how he or she would benefit from attending Cambridge Ellis Machine Learning Summer School. The referee should be a person that has some experience working together with the applicant. It can be for example a Ph.D. supervisor, a former employer or manager. 


José Miguel Hernández-Lobato
Kim Cole
Carl Henrick Ek
Carl Rasmussen