Self Supervised Learning (2024)
The Technical Doctoral School of IT and Design at Aalborg University
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