Further Probabilistic Modeling

The Cambridge Ellis Unit Summer School on Probabilistic Machine Learning is from 15-19 July 2024 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: 8 May 2024

Admission notification by:

22 May 2024

Topics

  • 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)

Danielle Belgrave
Soren Hauberg
Neil Laurance
Mike Tipping
Miles Cranmer
Carl Henrik Ek
Steven Morad
Cheng Zhang
Siyuan Guo
José Miguel Hernández-Lobato
Carl Rasmussen

Schedule

Please see the proposed schedule below.

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

Dates

Themes

M- 15 July 2024

Introduction to Probablistic Modeling

T- 16 July 2024

Probabilistic Models/Sequential Decision Making

W- 17 July 2024

Probabilistic Numerics

T- 18 July 2024

Implicit Models/Diffusion Models

F- 19 July 2024

Further Probabilistic Modeling

09.00 – 10.30

10.30 – 11.00

11.00 – 12.30

12.30 – 13.00 

13.00 – 14.30

14.30 – 16.00

16.00 – 16.30

16.30 – 17.30

17.30 – 19.00

19:00 – 22:00

Mike Tipping

Break

Carl Rasmussen

Lunch

Carl Henrik

TBA

Break

TBA

PANEL

Evening Dinner at Sidney Sussex College*

TBA

Break

Danielle Belgrave 

Lunch

Miles Cranmer 

TBA

Break

PANEL

Science Tour – 90 Min*

Steven Morad

Break

TBA

Lunch &

Poster

session

TBA

Break

TBA

PANEL

TBA

Break

TBA

Lunch 

Cheng Zhang

Miguel Hernández-Lobato

Break

PANEL

Cambridge Shakespeare Festival*

Siyuan Guo

Break

Soren Hauberg

Lunch

Neil Laurence

TBA

Poster Session & Farewell Reception

Venue

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.

Fees

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 ellis-admin@eng.cam.ac.uk for more information.

There are no fees to attend the Summer School.

Lunch and tea/coffee will be provided.

Apply

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. 

Organisers

José Miguel Hernández-Lobato
Catarina Araujo-Lopes
Carl Henrick Ek
Carl Rasmussen

Sponsors