Marloes Maathuis

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Markus KalischETH ZürichVerified email at stat.math.ethz.ch
Peter BühlmannProfessor of Statistics and Mathematics, ETH ZurichVerified email at stat.math.ethz.ch
Preetam NandyLinkedInVerified email at linkedin.com
Thomas S. RichardsonUniversity of WashingtonVerified email at uw.edu
Martin MächlerAdjunct Professor, ETH ZurichVerified email at stat.math.ethz.ch
Emilija PerkovićAssistant Professor, Department of Statistics, University of WashingtonVerified email at uw.edu
Daniel StekhovenNEXUS, ETH Zurich, SwitzerlandVerified email at nexus.ethz.ch
Mathias DrtonProfessor of Mathematical Statistics, Technical University of MunichVerified email at tum.de
Jon A. WellnerProfessor Emeritus of Statistics, University of WashingtonVerified email at stat.washington.edu
Piet GroeneboomVerified email at tudelft.nl
Nicolai MeinshausenProfessor of Statistics, ETH ZurichVerified email at stat.math.ethz.ch
Johannes TextorData Science Section, Institute for Computing and Information Sciences, Radboud University, NijmegenVerified email at radboudumc.nl
Olivia KeiserEpidemiologist, University of GenevaVerified email at unige.ch
Leonard HenckelUniversity of CopenhagenVerified email at math.ku.dk
balling rLuxembourg Centre for Systems Biomedicine (LCSB)Verified email at uni.lu
Teresa PrzytyckaNCBI / NLM / NIHVerified email at ncbi.nlm.nih.gov
Holger FröhlichHead of AI & Data Science Group & Deputy Head of Department of Bioinformatics at Fraunhofer SCAIVerified email at bit.uni-bonn.de
Rainer SpangUniversity of RegensburgVerified email at ur.de
Yves MoreauUniversity of LeuvenVerified email at esat.kuleuven.be
Andreas WeberProfessor of Computer Science, University of BonnVerified email at cs.uni-bonn.de

Marloes Maathuis

ETH Zurich

Verified email at stat.math.ethz.ch - Homepage

causal inference graphical models high-dimensional statistics applications


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Causal inference using graphical models with the R package pcalg M Kalisch, M Mächler, D Colombo, MH Maathuis, P Bühlmann Journal of Statistical Software 47 (11), 1-26, 2012	562	2012
Order-independent constraint-based causal structure learning. D Colombo, MH Maathuis J. Mach. Learn. Res. 15 (1), 3741-3782, 2014	424	2014
Learning high-dimensional directed acyclic graphs with latent and selection variables D Colombo, MH Maathuis, M Kalisch, TS Richardson Annals of Statistics 40, 294-321, 2012	349	2012
Estimating high-dimensional intervention effects from observational data MH Maathuis, M Kalisch, P Bühlmann The Annals of Statistics 37 (6A), 3133-3164, 2009	330	2009
Predicting causal effects in large-scale systems from observational data MH Maathuis, D Colombo, M Kalisch, P Bühlmann Nature Methods 7 (4), 247-248, 2010	270	2010
From hype to reality: data science enabling personalized medicine H Fröhlich, R Balling, N Beerenwinkel, O Kohlbacher, S Kumar, ... BMC medicine 16 (1), 1-15, 2018	207	2018
Structure learning in graphical modeling M Drton, MH Maathuis Annual Review of Statistics and Its Applications 4, 365-393, 2017	174	2017
Causal structure learning C Heinze-Deml, MH Maathuis, N Meinshausen Annual Review of Statistics and Its Application 5, 371-391, 2018	106	2018
Variable selection in high-dimensional linear models: partially faithful distributions and the pc-simple algorithm P Bühlmann, M Kalisch, MH Maathuis Biometrika 97 (2), 261-278, 2010	103	2010
Handbook of graphical models M Maathuis, M Drton, S Lauritzen, M Wainwright CRC Press, 2018	102	2018
High-dimensional consistency in score-based and hybrid structure learning P Nandy, A Hauser, MH Maathuis Annals of Statistics 46, 3151-3183, 2015	96	2015
A generalized back-door criterion MH Maathuis, D Colombo The Annals of Statistics 43 (3), 1060-1088, 2015	84	2015
Promises, pitfalls, and basic guidelines for applying machine learning classifiers to psychiatric imaging data, with autism as an example P Kassraian-Fard, C Matthis, JH Balsters, MH Maathuis, N Wenderoth Frontiers in psychiatry 7, 177, 2016	82	2016
Causal Stability Ranking DJ Stekhoven, L Hennig, G Sveinbjörnsson, I Moraes, MH Maathuis, ... Bioinformatics 28, 2819-2823, 2012	81	2012
Current status data with competing risks: consistency and rates of convergence of the MLE P Groeneboom, MH Maathuis, JA Wellner The Annals of Statistics 36, 1031-1063, 2008	69	2008
Reduction algorithm for the NPMLE for the distribution function of bivariate interval-censored data MH Maathuis Journal of Computational and Graphical Statistics 14 (2), 352-362, 2005	62	2005
Current status data with competing risks: limiting distribution of the MLE P Groeneboom, MH Maathuis, JA Wellner The Annals of Statistics 36, 1064-1089, 2008	61	2008
A combined statistical approach and ground movement model for improving taxi time estimations at airports S Ravizza, JAD Atkin, MH Maathuis, EK Burke Journal of the Operational Research Society, 1347-1360, 2012	60	2012
Complete graphical characterization and construction of adjustment sets in Markov equivalence classes of ancestral graphs E Perkovic, JC Textor, M Kalisch, MH Maathuis Journal of Machine Learning Research 18 (220), 1-62, 2018	59	2018
Estimating the effect of joint interventions from observational data in sparse high-dimensional settings P Nandy, MH Maathuis, TS Richardson The Annals of Statistics 45 (2), 647-674, 2017	57	2017

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