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<pdf width="1500px">https://ceur-ws.org/Vol-1274/uai2014ci_preface.pdf</pdf>
<pre>
Preface

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.
The aim of this workshop was to bring together researchers interested in the challenges of causal inference from observa-
tional 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 predic-
tions, 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.


October 2014                                                                                        Joris M. Mooij (Chair)
                                                                                                          Dominik Janzing
                                                                                                              Jonas Peters
                                                                                                             Tom Claassen
                                                                                                            Antti Hyttinen
Organizing Committee

 Joris M. Mooij        University of Amsterdam (Chair)
 Dominik Janzing       Max Planck Institute for Intelligent Systems
 Jonas Peters          ETH Zürich
 Tom Claassen          Radboud University Nijmegen
 Antti Hyttinen        California Institute of Technology

Program Committee

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