We are pleased to present the Proceedings of the UAI 2014 Workshop on Causal Inference: Learning and Prediction, held in Quebec City, Canada, on July 27, 2014, as a workshop of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014). This workshop is the third in a series of UAI workshops on the topic of causality, following up on two successful predecessors, the UAI Workshop on Causal Structure Learning 2012 and the Approaches to Causal Structure Learning Workshop, UAI 2013.

Abstract

The aim of this workshop was to bring together researchers interested in the challenges of causal inference from observational and interventional data, especially when confounding variables, feedback loops or selection bias may be present. For this workshop, we decided to extend the scope from causal structure learning to include methods for making causal predictions, i.e., for predicting what happens under interventions. We especially encouraged contributions describing practical applications of causal methods. There were 8 submissions, all full-length papers, each of which was peer-reviewed by two or three program committee members. We accepted five of these for oral presentation and for inclusion in these proceedings. The proceedings also include abstracts for three invited talks, including the two key-note talks by Robert Spekkens and Elias Bareinboim. Slides of most of the oral presentations are available on the workshop website: https://staff.fnwi.uva.nl/j.m.mooij/uai2014-causality-workshop/index.html We would like to thank the paper authors and presenters for their contributions and the program committee members for their reviewing service. We also appreciate the organizational support of the main UAI 2014 conference, in particular we would like to thank John Mark Agosta, Jin Tian and Ann Nicholson for their help. Further, we would like to thank Robin Evans, chair of the Approaches to Causal Structure Learning Workshop, UAI 2013, for his assistance. Finally, many thanks to the CEUR-WS team for hosting these proceedings.

Joris M. Mooij

Dominik Janzing Jonas Peters Tom Claassen Antti Hyttinen

University of Amsterdam (Chair) Max Planck Institute for Intelligent Systems ETH Zu¨ rich Radboud University Nijmegen

California Institute of Technology Program Committee

Thomas Richardson

Ricardo Silva Markus Kalisch Frederick Eberhardt Alain Hauser Ilya Shpitser Robin Evans Kun Zhang Eleni Sgouritsa Aapo Hyva¨rinen Jan Lemeire James Robins Chris Meek Preetam Nandy Philipp Geiger Nicholas Cornia Oliver Stegle University of Washington University College London ETH Zu¨ rich California Institute of Technology ETH Zu¨ rich University of Southampton University of Oxford Max Planck Institute for Intelligent Systems Max Planck Institute for Intelligent Systems University of Helsinki Vrije Universiteit Brussel Harvard School of Public Health Microsoft Research ETH Zu¨ rich Max Planck Institute for Intelligent Systems University of Amsterdam The European Bioinformatics Institute

References