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
Admission notification by: 15 May 2023
Admission notification by: 5 June 2023
We can no longer accept applications
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)
Schedule
Please see the proposed schedule below.
Items followed by * are arranged by the organisers but need to paid for separately.
Dates
M- 17 July 2023
T- 18 July 2023
W- 19 July 2023
Th- 20 July 2023
F- 21 July 2023
Themes
Introduction to Probablistic Modeling
Probabilistic Models/Sequential Decision Making
Probabilistic Numerics
Implicit Models/Diffusion Models
Further Probabilistic Modeling
09:00
Mark van der Wilk
Henry Moss- BayesOpt and Beyond: Optimization of Expensive Functions using Gaussian Processes
Rich Turner- Neural Processes for Environmental Research
09:30
10:00
Break
11:30
12:00
Lunch
Lunch
12:30
Lunch
Lunch
Tian Xie- Challenges and opportunities in accelerating materials design with geometric deep learning and generative models
Marc Deisenroth
13:30
14:00
Lunch
15:00
Break
Break
Neill Campbell- Probabilistic Generative and Compositional Models
15:30
Poster Session & Farewell Reception
16:00
16:30
17:15
Science Tour- 90 min*
19:00-22:00
Evening Dinner at Sidney Sussex College*
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
Sponsors
