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Teaser image to 3rd MCML Workshop on Causal Machine Learning

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

Break

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

Coffee Break

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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