Self Supervised Learning (2024)

Welcome to Self-Supervised Learning

Organizer: Zheng-Hua Tan

Lecturers: Zheng-Hua Tan

ECTS: 2

Date/Time: November 18-20, 2024

Deadline: 28 October 2024

Max no. Of participants: 50

Description: The course gives an introduction to self-supervised learning methods for learning representations of single- and multiple-modality data, covering deep architectures, training target and loss functions used in state-of-the-art methods, and selected downstream applications. A focus will be given to loss functions including both contrastive and predictive losses.

Prerequisites: Knowledge in machine learning or deep learning and basic skills in Python programming

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.