Deep learning is a subfield of machine learning that has achieved significant state-of-the-art results in many areas of artificial intelligence, including computer vision and robotics, and has been advancing very quickly in recent years. This seminar aims to cover introductory topics in the field of deep learning. It takes shape as a paper reading and discussing the concept of "learning and learning". A collection of papers from selected journals and conferences is provided for the students to choose from. In each meeting, two topics are presented by the students.
Students are graded based on: a) their presentation, b) a short report that they write on the subject, and c) their participation in post-presentation discussions. So, attendance is required to pass the course.
The date for the first meeting can be seen from the table above. In the session, each student chooses one topic and the presentations will start after two weeks; one presentation in each meeting. Participation in the preliminary meeting is required. If you are unable to attend this session, please write a mail to daniel.weberspam prevention@uni-tuebingen.de.
Important note: Since there is a maximum number of 12 participants in this course, please register in ILIAS as soon as possible if you are interesting in taking the seminar.
