Welcome to the Munich Workshop on Causal Inference and Information Theory (MCI) on May 23rd & 24th 2016

Causal inference (including measures of causality, causal modeling, and structure learning), has received considerable attention in the recent years from researchers in information theory, economics, philosophy, and machine learning. The goal of this workshop is to bring together outstanding researchers from these areas in order to discuss possible interconnections between their viewpoints and approaches.

Confirmed Speakers

• Elias Bareinboim (Purdue University)
• Frederick Eberhardt (Caltech)
• Michael Eichler (Maastricht University)
• Dominik Janzing (Max-Planck-Institute, Tuebingen)
• Young-Han Kim (University of California, San Diego)
• Haim Permuter (Ben Gurion University)
• Christopher Quinn (Purdue University)
• Thomas Richardson (University of Washington)
• Shohei Shimizu (Osaka University)

Program

Monday, May 23rd
09:00-09:15	Opening Remarks by Gerhard Kramer
09:15-10:00	Kun Zhang	Practical Considerations in Causal Discovery: Confounders, Time-Varying Causal Relations, and Selection Bias
10:00-10:45	Chris Quinn	Learning and Approximating (Granger) Causal Influences in Networks
10:45-11:00	Coffee Break
11:00-11:45	Young-Han Kim	How to Learn Probability without Learning
11:45-12:30	Shohei Shimizu	A non-Gaussian Model for Causal Discovery in the Presence of Hidden Common Causes
12:30-14:30	Lunch Break Table booked (20 px) at Pizzeria Coccinella, ~7,50 Euro per pizza
14:30-15:15	Haim Permuter	Causal Conditioning and Directed Information in Engineering Problems
15:15-16:00	Michael Eichler	Causal Inference from Multivariate Time Series: Principles and Problems
16:00-16:15	Coffee Break
16:15-17:00	Thomas Richardson	Learning Causal Structure in the Presence of Hidden Variables
17:00-18:00	Discussion led by Negar Kiyavash
19:00-	Table booked (30 px) at Max Emanuel, a local brewery with a nice beergarden
Tuesday, May 24th
09:15-10:00	Frederick Eberhardt	Generalized Constraint Based Causal Discovery and Causal Macro-Variables
10:00-10:45	Dominik Janzing	Algorithmic Independence of Cause and Mechanism as a Common Footing of Thermodynamics and Causal Inference
10:45-11:00	Coffee Break
11:00-11:45	Elias Bareinboim	Causal Inference and the Data-Fusion Problem
11:45-12:30	Discussion led by Kun Zhang

Directions

• Metro map Munich.
• Airport to Hotel Königswache: use S8 to Herrsching. Get off at Hauptbahnhof and take the U2 to Feldmoching. Get off at Theresienstraße and walk to Hotel Königswache. We recommend the Airport-City-Day-Ticket since it allows you to use the public transport in Munich during the whole day.
• You can also walk from Hauptbahnhof to Hotel Königswache.
• Walk from Hotel Königswache to the LNT.
• At the LNT, take the elevator or stairs to the 2nd floor. The talks will be given in the seminar room N2408.

Registration

The workshop features invited talks only, attendance is free of charge. If you are interested in attending, please send an email to geiger(at)ieee.org.

Organizers

• Negar Kiyavash (University of Illinois Urbana-Champaign and TUM)
• Gerhard Kramer (TUM)
• Kun Zhang (Carnegie Mellon University)
• Bernhard C. Geiger (TUM)
• Jalal Etesami (University of Illinois Urbana-Champaign and TUM)

Supported by

Photos