| Estimating high-dimensional directed acyclic graphs with the PC-algorithm M Kalisch, P Bühlmann Journal of Machine Learning Research 8 (Mar), 613-636, 2007 | 690 | 2007 |
| 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 | 426 | 2012 |
| Estimating high-dimensional intervention effects from observational data MH Maathuis, M Kalisch, P Bühlmann The Annals of Statistics 37 (6A), 3133-3164, 2009 | 273 | 2009 |
| Learning high-dimensional directed acyclic graphs with latent and selection variables D Colombo, MH Maathuis, M Kalisch, TS Richardson The Annals of Statistics, 294-321, 2012 | 252 | 2012 |
| 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 | 243 | 2010 |
| High-dimensional statistics with a view toward applications in biology P Bühlmann, M Kalisch, L Meier Annual Reviews, 2014 | 208 | 2014 |
| Selection of carbonic anhydrase IX inhibitors from one million DNA-encoded compounds F Buller, M Steiner, K Frey, D Mircsof, J Scheuermann, M Kalisch, ... ACS chemical biology 6 (4), 336-344, 2011 | 113 | 2011 |
| 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 | 85 | 2010 |
| Robustification of the PC-algorithm for directed acyclic graphs M Kalisch, P Bühlmann Journal of Computational and Graphical Statistics 17 (4), 773-789, 2008 | 62 | 2008 |
| The Penile Perception Score: an instrument enabling evaluation by surgeons and patient self-assessment after hypospadias repair DM Weber, MA Landolt, R Gobet, M Kalisch, NK Greeff The Journal of urology 189 (1), 189-193, 2013 | 56 | 2013 |
| Understanding human functioning using graphical models M Kalisch, BAG Fellinghauer, E Grill, MH Maathuis, U Mansmann, ... BMC Medical Research Methodology 10 (1), 14, 2010 | 50 | 2010 |
| A complete generalized adjustment criterion E Perković, J Textor, M Kalisch, MH Maathuis arXiv preprint arXiv:1507.01524, 2015 | 41 | 2015 |
| Robustified L2 boosting RW Lutz, M Kalisch, P Bühlmann Computational Statistics & Data Analysis 52 (7), 3331-3341, 2008 | 36 | 2008 |
| Causal structure learning and inference: a selective review M Kalisch, P Bühlmann Quality Technology & Quantitative Management 11 (1), 3-21, 2014 | 33 | 2014 |
| Complete graphical characterization and construction of adjustment sets in Markov equivalence classes of ancestral graphs E Perkovic, J Textor, M Kalisch, MH Maathuis The Journal of Machine Learning Research 18 (1), 8132-8193, 2017 | 31 | 2017 |
| Assessing statistical significance in multivariable genome wide association analysis L Buzdugan, M Kalisch, A Navarro, D Schunk, E Fehr, P Bühlmann Bioinformatics 32 (13), 1990-2000, 2016 | 29 | 2016 |
| Decomposition and model selection for large contingency tables C Dahinden, M Kalisch, P Bühlmann Biometrical Journal: Journal of Mathematical Methods in Biosciences 52 (2 …, 2010 | 24 | 2010 |
| Diode-pumped passively mode-locked Nd: YVO/sub 4/lasers with 40-GHz repetition rate S Lecomte, M Kalisch, L Krainer, GJ Spuhler, R Paschotta, M Golling, ... IEEE journal of quantum electronics 41 (1), 45-52, 2005 | 24 | 2005 |
| Interpreting and using CPDAGs with background knowledge E Perković, M Kalisch, MH Maathuis arXiv preprint arXiv:1707.02171, 2017 | 21 | 2017 |
| pcalg: Estimation of CPDAG/PAG and causal inference using the IDA algorithm M Kalisch, M Mächler, D Colombo UR L http://CRAN. R-project. org/package= pcalg. R package version, 1-1, 2010 | 17 | 2010 |
Peter BühlmannProfessor of Statistics and Mathematics, ETH ZurichBestätigte E-Mail-Adresse bei stat.math.ethz.ch
