Topic outline

  • Completing the course gives 5 ECTS points.

    You can get 2 extra ECTS points by completing an optional small project:
    • The work should be done in groups of 1-4 people
    • Hand-in a detailed project report (one per group) no later than 12th of March
    • Give a 10-20min presentation of your work on a project session on 18th of March at 10:15am

    The project work is supported by four sessions:
    • There is a project kick-off session on thursday 18th february 10:15
    • There is a support session on thursday 4th of March 10:15 for Q&A
    • There is a final project work seminar on 18th of March with group presentations (10-20 min)

    The project work topics are:
    1. Iterative kernel learning
    2. Bayesian optimization with Gaussian Processes
    3. Bayesian quadrature
    4. Relationship between Neural networks and GPs
    5. Multioutput Gaussian processes & Kronecker structures
    6. Gaussian processes for big data
    7. Gaussian processes with monotonicity
    8. Gaussian process latent variable model (GPLVM)
    9. Convolutional Gaussian processes
    10. Gaussian process inference (eg. VI, EP, MCMC)
    11. Deep Gaussian processes
    12. State-space GPs
    13. Dynamical GPs
    14. Own topic (contact Markus/Arno)

    The project work consist of one of following tasks
    1. Analyze your favourite dataset with Gaussian process models of you topic
    2. Literature survey/comparison of more advanced Gaussian process models/methods of your topic
    3. Implementation of more advanced Gaussian process models of your topic

    In the first task you should compare the GP model(s) against other baseline methods. Study the inference of the GP model, and study the predictive posteriors of your GP model in your dataset. In the second task read about your topic from scientific literature. Discuss the topic in depth. In the third task choose your favourite programming language and/or library, and implement an advanced GP model of your topic. Describe your implementation and test it.  

    Please form a group, pick 1 topic and 1 task:
    • Come to the kick-off session on Feb 18th 10:15. We will introduce the topics, and you can form groups at the sessions, and discuss the project.
    • Please report your group/topic to