MCML Workshop
3rd MCML Workshop on Causal Machine Learning
Organized by Our PI Stefan Feuerriegel and His Team
07.08.2024
11:00 am - 8:00 pm
LMU Munich, Professor-Huber-Platz 2, W201
Causal inference has become highly important in many fields, such as medicine or marketing, and has received increasing attention from researchers in machine learning in recent years. The MCML Workshop in Causal Machine Learning invites causal ML researchers to present their work. The workshop aims to bring together researchers from different fields to discuss possible interconnections between their work and foster future collaborations.
Participation
Participation is open to all MCML members as well as researchers from other institutions. To register for the workshop, please send an email to Maresa Schröder by 28.07.2024.
Research Presentation
Participants are invited to give a talk on their research work in a 20-minute presentation (+ 10-minute Q&A). As presentation slots are limited, we kindly ask interested participants to apply for a presentation with a title and abstract of the work via email to Stefan Feuerriegel by 21.07.2024. Presentations will be selected based on scientific quality but also diversity.
Schedule
11:00 am – 11:15 am
Welcome
Stefan Feuerriegel, LMU
11:15 am – 12:00 pm
Tutorial: Causal discovery
Stefan Bauer, Helmholtz/TUM
12:00 pm – 12:30 pm
Keynote: Improving AI Safety with Causal Machine Learning
Francesco Quinzan, Oxford
12:30 pm – 2:00 pm
Lunch break (lunch not provided)
Coffee will be served from 13:30 in the seminar room
2:00 pm – 2:45 pm
Tutorial: Causal ML for treatment effect estimation
Valentyn Melnychuk, LMU
2:45 pm – 3:00 pm
3:00 pm – 3:15 pm
Lab presentation: Social Data Science and AI Lab
Christoph Kern, LMU
3:15 pm – 3:30 pm
Lab presentation: AI in Medical Imaging
Christian Wachinger, TUM
3:30 pm – 4:00 pm
Unpaired Multi-Domain Causal Representation Learning
Nils Sturma, TUM
4:00 pm – 4:15 pm
4:15 pm – 4:45 pm
Conformal Prediction for Causal Effects
Maresa Schröder, LMU
4:45 pm – 5:15 pm
Hierarchical High Dimensional Synthetic Causal Data Generation
Xundong Sun & Alex Markham, Helmholtz / KTH
5:15 pm – 5:30 pm
Break
5:30 pm – 6:00 pm
Causal Inference with Cocycles
Hugh Dance, UCL
6:00 pm – 6:30 pm
Evaluation of Active Feature Acquisition Methods
Henrik von Kleist, Helmholtz/TUM
6:30 pm – 8:00 pm
Dinner & Networking (beer garden; at own expenses)
Organized by:
Stefan Feuerriegel and team
MCML / Institute of AI in Management , LMU Munich
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