Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage
At the end of the course, the students will be able to read and critique scientific papers. They will be able to analyse the methods proposed in the field of neuroscience-based AI, and evaluate their strengths and weaknesses. They will be able to prepare an oral presentation of their findings and discuss the studied methods in detail. Finally, they will be able to assess their peers’ work.
The seminar will cover topics belonging to a relevant subfield of machine learning and artificial intelligence (AI): neuroscience-inspired AI.The course will explore the intersection of computational neuroscience and machine learning, examining how they can help advance AI. Computational neuroscience uses mathematical models of the brain to understand the principles that govern neural systems. Combined with machine learning, it enables the development of algorithms that can model neural processing, offering insights into both neuroscience and AI. Typical problems include decoding the computation behind neural activity or deriving learning mechanisms that are biologically plausible. Key areas of focus for this seminar include:
Die Studierenden müssen
Students attend the kick-off meeting. In the kick-off meeting, each student is allocated to a topic and a paper. After the kick-off meeting, each student is expected to read the assigned paper and the papers belonging to their topic, and to perform a literature review of the related work. Four weeks after the kick-off meeting, each student is expected to schedule a meeting with their advisor to discuss their findings. In June, there will be a presentation day. During the presentation day, each student is expected to prepare a 25 min presentation where their findings are summarised (which is followed by a 5-10 min discussion). After the presentation, students are given feedback on their presentation and seminar paper. Each student will write a seminar paper (6-7 pages + references) on their topic, where the central ideas and methods presented in the talk are summarised.
Prüfungsimmanent.