Seminar Explainable Machine Learning
(Winter term 2026/27)
Who, when, where
Who: Ulrike von Luxburg together with Maximilian Thiessen and Gunnar König When: Wednesdays 14:15 - 16:00 and two compact days, details tba. Where: Maria-von-Linden-Strasse, 1 tba. Language: English Credit points: 3 CPDescription
Modern machine, learning methods, such as deep learning, random forests, or XGBoost typically produce ``black box models'': they can excel at prediction, but it is completely unclear on which criteria these predictions are being based. While there are many applications where this might not be an issue, there are others where a deeper understanding of the models is necessary: applications in medicine, applications in society (say, credit scoring), or applications in science, where we want to understand the underlying processes. Also, from the legal point of view, explanations are arguably requested in the new AI Act that regulates machine learning applications, and explanations are often considered as a means to establish trust in machine learning applications. The field of explainable machine learning, often abbreviated as XAI, tries to develop methods and algorithms that supposedly produce explanations for machine learning models. In this seminar, we are going to discuss many of the standard approaches in this field. We will also discuss critically whether and under which conditions the suggested methods might achieve their goal or not.Prerequesits
This seminar is intended for master students in machine learning, computer science or related fields. Basic knowledge on machine learning, for example at least one of the standard classes in the ML master program, is required.Registration
Tba.Organization
- Phase 1 (Mid Oct - Mid Nov): During the first four weeks, the seminar proceeds as a lecture: Ulrike Luxburg and two of her postdocs give an overview on the basic methods and questions in the field.
- Phase 2 (Mid Nov - End Dec): The seminar participants work on their individual presentations.
- Phase 3 (Jan): Presentations take place on two whole days (dates tba). Presentations need to be in english.
To pass the seminar, each participant has to give a presentation, needs to act as sparring partner for another paper, and needs to be present at the compact seminar days. Details will be explained during the seminar.
Schedule
Tentative and subject to change:- 12.10. Lecture 1 (Ulrike von Luxburg): Introduction to XAI, setup of this seminar.
- 19.10. Lecture 2 (Gunnar König): Conflicting XAI Goals, Contrastive Explanations, Global Methods.
- 26.10. Lecture 3 (Maximilian Thiessen): Tba.
- One day in January. All day: presentations by seminar participants.
- Another day in Januar. All day: Presentations by seminar participants.
