Nicolai Meinshausen

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Peter BühlmannProfessor of Statistics and Mathematics, ETH ZurichVerified email at stat.math.ethz.ch
Malte MeinshausenProf, University of MelbourneVerified email at unimelb.edu.au
Reto KnuttiProfessor for Climate Physics, ETH ZurichVerified email at env.ethz.ch
Jonas PetersProfessor of Statistics, ETH ZurichVerified email at stat.math.ethz.ch
Christina Heinze-DemlApple AI/ML ResearchVerified email at apple.com
Elisabeth VogelWater Research Centre, UNSWVerified email at unsw.edu.au
Erich FischerETH ZurichVerified email at env.ethz.ch
Sebastian SippelLeipzig UniversityVerified email at uni-leipzig.de
Bin YUProfessor of Statistics and EECS, UC BerkeleyVerified email at stat.berkeley.edu
Dominik RothenhäuslerStanford UniversityVerified email at stanford.edu
Lukas MeierETH ZürichVerified email at stat.math.ethz.ch
Rajen D. ShahUniversity of CambridgeVerified email at cam.ac.uk
Brian McWilliamsGoogle DeepMindVerified email at google.com
Angeline G PendergrassCornell University and National Center for Atmospheric ResearchVerified email at ucar.edu
Ben HamblyProfessor of Mathematics, University of OxfordVerified email at maths.ox.ac.uk
Joris M. MooijProfessor in Mathematical Statistics, Korteweg-de Vries Institute, University of Amsterdam (NL)Verified email at uva.nl
Gareth BondUniversity of OxfordVerified email at ndm.ox.ac.uk
Mathias DrtonProfessor of Mathematical Statistics, Technical University of MunichVerified email at tum.de
Luca WeihsResearch Scientist, Allen Institute for Artificial IntelligenceVerified email at allenai.org
Xinwei ShenETH ZurichVerified email at stat.math.ethz.ch

Nicolai Meinshausen

Professor of Statistics, ETH Zurich

Verified email at stat.math.ethz.ch

Causality Machine Learning High-Dimensional Data Computational Statistics


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High-dimensional graphs and variable selection with the lasso N Meinshausen, P Bühlmann The Annals of Statistics 34 (3), 1436-1462, 2006	4568	2006
Greenhouse-gas emission targets for limiting global warming to 2 C M Meinshausen, N Meinshausen, W Hare, SCB Raper, K Frieler, R Knutti, ... Nature 458 (7242), 1158-1162, 2009	3723	2009
Stability selection N Meinshausen, P Bühlmann Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2010	3007	2010
Quantile regression forests N Meinshausen The Journal of Machine Learning Research 7, 983-999, 2006	2157	2006
Warming caused by cumulative carbon emissions towards the trillionth tonne MR Allen, DJ Frame, C Huntingford, CD Jones, JA Lowe, M Meinshausen, ... Nature 458 (7242), 1163-1166, 2009	2001	2009
Lasso-type recovery of sparse representations for high-dimensional data N Meinshausen, B Yu The Annals of Statistics 37 (1), 246-270, 2009	1059	2009
Causal inference by using invariant prediction: identification and confidence intervals J Peters, P Bühlmann, N Meinshausen Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2016	1033	2016
The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500 M Meinshausen, ZRJ Nicholls, J Lewis, MJ Gidden, E Vogel, M Freund, ... Geoscientific Model Development 13 (8), 3571-3605, 2020	983*	2020
Relaxed lasso N Meinshausen Computational Statistics & Data Analysis 52 (1), 374-393, 2007	968	2007
The effects of climate extremes on global agricultural yields E Vogel, MG Donat, LV Alexander, M Meinshausen, DK Ray, D Karoly, ... Environmental Research Letters 14 (5), 054010, 2019	626	2019
P-values for high-dimensional regression N Meinshausen, L Meier, P Bühlmann Journal of the American Statistical Association 104 (488), 1671-1681, 2009	465	2009
Historical greenhouse gas concentrations for climate modelling (CMIP6) M Meinshausen, E Vogel, A Nauels, K Lorbacher, N Meinshausen, ... Geoscientific Model Development 10 (5), 2057-2116, 2017	415	2017
High-dimensional inference: confidence intervals, p-values and R-software hdi R Dezeure, P Bühlmann, L Meier, N Meinshausen Statistical science, 533-558, 2015	327	2015
Invariant causal prediction for nonlinear models C Heinze-Deml, J Peters, N Meinshausen Journal of Causal Inference 6 (2), 20170016, 2018	281	2018
Climate change now detectable from any single day of weather at global scale S Sippel, N Meinshausen, EM Fischer, E Székely, R Knutti Nature climate change 10 (1), 35-41, 2020	256	2020
Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses N Meinshausen, J Rice The Annals of Statistics 34 (1), 373-393, 2006	256	2006
Causal structure learning C Heinze-Deml, MH Maathuis, N Meinshausen Annual Review of Statistics and Its Application 5 (1), 371-391, 2018	237	2018
Anchor regression: Heterogeneous data meet causality (vol 83, pg 215, 2021) D Rothenhausler, N Meinshausen, P Buhlmann, J Peters JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 83 …, 2021	224*	2021
Hierarchical testing of variable importance N Meinshausen Biometrika 95 (2), 265-278, 2008	208	2008
MONTE CARLO METHODS FOR THE VALUATION OF MULTIPLE‐EXERCISE OPTIONS N Meinshausen, BM Hambly Mathematical Finance 14 (4), 557-583, 2004	199	2004

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