4th MCML Workshop on Causal Machine Learning

10:00 am – 10:15 am

Welcome

Stefan Feuerriegel, LMU

10:15 am – 11:15 am

Tutorial: DoubleML (https://docs.doubleml.org/stable/index.html)

Martin Spindler, Sven Klaassen, Economic AI

11:15 am – 11:45 am

Adjustment for Confounding using Pre-Trained Representations

Rickmer Schulte, LMU Munich

11:45 am – 1:15 pm

Lunch Break (lunch not provided)

Coffee will be served from 13:00 in the seminar room

1:15 pm – 2:15 pm

Keynote

Deep Learning and Causality: Bridging the Gap

Rahul G. Krishnan, University of Toronto

2:15 pm – 2:30 pm

Lab Presentation

Mathias Drton, TU Munich

2:30 pm – 3:00 pm

3:00 pm – 3:30 pm

Foundation Models for Causal Inference via Prior-Data Fitted Networks

Emil Javurek, LMU Munich

3:30 pm – 4:00 pm

Estimating Treatment Effects with Independent Component Analysis

Patrik Reizinger, Max Planck Institute

4:00 pm – 4:30 pm

4:30 pm – 5:00 pm

Causal Strategic Learning with Competitive Selection

Huynh Vo, Helmholtz-Zentrum

5:00 pm – 5:15 pm

Heterogeneous Treatment Effects in Survival Data: Application to Real-World-Data in the Context of Regulatory Decision-Making

Anna Weller, Fraunhofer (Short presentation)

5:15 pm – 5:30 pm

Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing

Oliver Schacht, University of Hamburg (Short presentation)

5:30 pm – 8:00 pm

Dinner & Networking 🥨

Beer garden; at own expenses