Recent Advances in Machine Learning

This module will present recent advances in machine learning in different fields of data sciences including imaging, vision, graphics, mechatronics, and sensorics. It addresses advanced techniques in the fields of machine learning, deep learning and artificial intelligence, with a particular focus on recent research papers, novel application areas and open questions in the aforementioned fields. Based on basic prior knowledge gained in other courses, this module specifically focuses on the state-of-the-art in machine learning by introducing recent publications from the leading international conferences on machine learning (e.g. NeurIPS, ICML, ICLR), computer vision (e.g. CVPR, ICCV, ECCV), or their application in fields like computer graphics, 3d reconstruction, robotics, navigation, medicine, or body-worn sensorics. After covering the theory of such works in the first half of the semester, a phase with challenges will ask every student to implement and apply one of the discussed techniques on their own in one of the leading machine learning frameworks in the second half of the semester. The results of the challenges need to be presented to the class, and a short final report on the challenge will be the courses examination. 

This will be an exciting interdisciplinary lecture for advanced master students from mechatronics and computer science!