Seminar CS 717: Understanding Explainable AI Methods (HWS 2026)

This seminar will cover Explainable AI methods, with particular emphasis on Concept Bottleneck Models (CBMs), their architecture, and practical applications.
It will also explore how CBMs enhance interpretability by linking high-level human concepts with machine learning predictions.

In this seminar, you will

• Read, understand, and explore scientific literature
• Summarize a current research topic in a concise report (10 single-column pages + references)
• Give two presentations about your topic (3 minutes flash presentation, 15 minutes detailed presentation)
• Moderate a scientific discussion about the topic of one of your fellow students
• Review a (draft of a) report of a fellow student

• This seminar is organized by Prof. Dr.-Ing. Margret Keuper
• Prerequisites:  Background in Machine Learning
• Maximum number of participants is 6 Master's students

Seminar Schedule is provided here : Schedule (PDF, 189 kB)