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.

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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.

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Schedule

11:00 – 11:15	Welcome Stefan Feuerriegel, LMU
11:15 – 12:00	Tutorial: Causal discovery Stefan Bauer, Helmholtz/TUM
12:00 – 12:30	Keynote: Improving AI Safety with Causal Machine Learning Francesco Quinzan, Oxford
12:30 – 14:00	Lunch break (lunch not provided) Coffee will be served from 13:30 in the seminar room
14:00 – 14:45	Tutorial: Causal ML for treatment effect estimation Valentyn Melnychuk, LMU
14:45 - 15:00	Break
15:00 – 15:15	Lab presentation: Social Data Science and AI Lab Christoph Kern, LMU
15:15 - 15:30	Lab presentation: AI in Medical Imaging Christian Wachinger, TUM
15:30 – 16:00	Unpaired Multi-Domain Causal Representation Learning Nils Sturma, TUM
16:00 – 16:15	Coffee break
16:15 – 16:45	Conformal Prediction for Causal Effects Maresa Schröder, LMU
16:45 – 17:15	Hierarchical High Dimensional Synthetic Causal Data Generation Xundong Sun & Alex Markham, Helmholtz / KTH
17:15 – 17:30	Break
17:30 – 18:00	Causal Inference with Cocycles Hugh Dance, UCL
18:00 – 18:30	Evaluation of Active Feature Acquisition Methods Henrik von Kleist, Helmholtz/TUM
18:30 - 20:00	Dinner & networking (beer garden; at own expenses)