Peter Bühlmann

70 papers A* 1A 1Journal 65Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Causal chambers as a real-world physical testbed for AI methodology. Nat. Mac. Intell. Juan L. Gamella, Jonas Peters, Peter Bühlmann
2025	J	`jnl`	Causality-Inspired Robustness for Nonlinear Models via Representation Learning. CoRR Marin Sola, Peter Bühlmann, Xinwei Shen
2025	J	`jnl`	Domain Generalization and Adaptation in Intensive Care with Anchor Regression. CoRR Malte Londschien, Manuel Burger, Gunnar Rätsch, Peter Bühlmann
2025	J	`jnl`	Natural Language-Based Synthetic Data Generation for Cluster Analysis. J. Classif. Michael J. Zellinger, Peter Bühlmann
2025	J	`jnl`	TSCI: Two Stage Curvature Identification for Causal Inference with Invalid Instruments in J. Stat. Softw. David Carl, Corinne Emmenegger, Peter Bühlmann, Zijian Guo
2024	J	`jnl`	Assessing the Overall and Partial Causal Well-Specification of Nonlinear Additive Noise Models. J. Mach. Learn. Res. Christoph Schultheiss, Peter Bühlmann
2024	J	`jnl`	Causal Invariance Learning via Efficient Optimization of a Nonconvex Objective. CoRR Zhenyu Wang, Yifan Hu, Peter Bühlmann, Zijian Guo
2024	J	`jnl`	Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning. CoRR Yihong Gu, Cong Fang, Peter Bühlmann, Jianqing Fan
2024	J	`jnl`	Learning and scoring Gaussian latent variable causal models with unknown additive interventions. J. Mach. Learn. Res. Armeen Taeb, Juan L. Gamella, Christina Heinze-Deml, Peter Bühlmann
2024	J	`jnl`	Optimistic Search: Change Point Estimation for Large-scale Data via Adaptive Logarithmic Queries. J. Mach. Learn. Res. Solt Kovács, Housen Li, Lorenz Haubner, Axel Munk, Peter Bühlmann
2024	J	`jnl`	The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology. CoRR Juan L. Gamella, Jonas Peters, Peter Bühlmann
2023	J	`jnl`	Causality-oriented robustness: exploiting general additive interventions. CoRR Xinwei Shen, Peter Bühlmann, Armeen Taeb
2023	J	`jnl`	Confidence and Uncertainty Assessment for Distributional Random Forests. J. Mach. Learn. Res. Jeffrey Näf, Corinne Emmenegger, Peter Bühlmann, Nicolai Meinshausen
2023	J	`jnl`	Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics. WIREs Data Mining Knowl. Discov. Fernando Marmolejo-Ramos, Mauricio Tejo, Marek Brabec, Jakub Kuzilek, Srecko Joksimovic, Vitomir Kovanovic, Jorge González, Thomas Kneib, Peter Bühlmann, Lucas Kook, Guillermo Briseño-Sánchez, Raydonal Ospina
2023	J	`jnl`	Distributionally Robust Machine Learning with Multi-source Data. CoRR Zhenyu Wang, Peter Bühlmann, Zijian Guo
2023	J	`jnl`	Invariant Probabilistic Prediction. CoRR Alexander Henzi, Xinwei Shen, Michael Law, Peter Bühlmann
2023	A*	`conf`	On the Identifiability and Estimation of Causal Location-Scale Noise Models. ICML Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
2023	J	`jnl`	Random Forests for Change Point Detection. J. Mach. Learn. Res. Malte Londschien, Peter Bühlmann, Solt Kovács
2023	J	`jnl`	repliclust: Synthetic Data for Cluster Analysis. CoRR Michael J. Zellinger, Peter Bühlmann
2022	J	`jnl`	Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression. J. Mach. Learn. Res. Domagoj Cevid, Loris Michel, Jeffrey Näf, Peter Bühlmann, Nicolai Meinshausen
2022	J	`jnl`	Distributional anchor regression. Stat. Comput. Lucas Kook, Beate Sick, Peter Bühlmann
2022	J	`jnl`	Identifying cancer pathway dysregulations using differential causal effects. Bioinform. Kim Philipp Jablonski, Martin Pirkl, Domagoj Cevid, Peter Bühlmann, Niko Beerenwinkel
2022	J	`jnl`	On the Identifiability and Estimation of Causal Location-Scale Noise Models. CoRR Alexander Immer, Christoph Schultheiss, Julia E. Vogt, Bernhard Schölkopf, Peter Bühlmann, Alexander Marx
2022	J	`jnl`	Structure Learning for Directed Trees. J. Mach. Learn. Res. Martin Emil Jakobsen, Rajen Dinesh Shah, Peter Bühlmann, Jonas Peters
2022	J	`jnl`	The Weighted Generalised Covariance Measure. J. Mach. Learn. Res. Cyrill Scheidegger, Julia Hörrmann, Peter Bühlmann
2021	J	`jnl`	Change-Point Detection for Graphical Models in the Presence of Missing Values. J. Comput. Graph. Stat. Malte Londschien, Solt Kovács, Peter Bühlmann
2021	J	`jnl`	Domain adaptation under structural causal models. J. Mach. Learn. Res. Yuansi Chen, Peter Bühlmann
2021	J	`jnl`	Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning. CoRR Michael Moor, Nicolas Bennett, Drago Plecko, Max Horn, Bastian Rieck, Nicolai Meinshausen, Peter Bühlmann, Karsten M. Borgwardt
2021	J	`jnl`	Structure Learning for Directed Trees. CoRR Martin Emil Jakobsen, Rajen Dinesh Shah, Peter Bühlmann, Jonas Peters
2020	J	`jnl`	Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression. CoRR Domagoj Cevid, Loris Michel, Nicolai Meinshausen, Peter Bühlmann
2020	J	`jnl`	Domain adaptation under structural causal models. CoRR Yuansi Chen, Peter Bühlmann
2020	J	`jnl`	Hierarchical inference for genome-wide association studies: a view on methodology with software. Comput. Stat. Claude Renaux, Laura Buzdugan, Markus Kalisch, Peter Bühlmann
2020	J	`jnl`	Optimistic search strategy: Change point detection for large-scale data via adaptive logarithmic queries. CoRR Solt Kovács, Housen Li, Lorenz Haubner, Axel Munk, Peter Bühlmann
2020	J	`jnl`	Rejoinder on: Hierarchical inference for genome-wide association studies: a view on methodology with software. Comput. Stat. Claude Renaux, Laura Buzdugan, Markus Kalisch, Peter Bühlmann
2020	—	`conf`	SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research. MIE Adrian Egli, Manuel Battegay, Andrea C. Büchler, Peter Bühlmann, Thierry Calandra, Philippe Eckert, Hansjakob Furrer, Gilbert Greub, Stephan M. Jakob, Laurent Kaiser, Stephen L. Leib, Stephan Marsch, Nicolai Meinshausen, Jean-Luc Pagani, Jerome Pugin, Gunnar Rätsch, Jacques Schrenzel, Reto Schüpbach, Martin Siegemund, Nicola Zamboni, Reinhard Zbinden, Annelies Zinkernagel, Karsten M. Borgwardt
2019	J	`jnl`	Change point detection for graphical models in presence of missing values. CoRR Malte Londschien, Solt Kovács, Peter Bühlmann
2019	J	`jnl`	Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise. J. Mach. Learn. Res. Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
2018	J	`jnl`	groupICA: Independent component analysis for grouped data. CoRR Niklas Pfister, Sebastian Weichwald, Peter Bühlmann, Bernhard Schölkopf
2016	J	`jnl`	Assessing statistical significance in multivariable genome wide association analysis. Bioinform. Laura Buzdugan, Markus Kalisch, Arcadi Navarro, Daniel Schunk, Ernst Fehr, Peter Bühlmann
2016	—	`book`	Handbook of Big Data. Peter Bühlmann, Petros Drineas, Michael J. Kane, Mark J. van der Laan
2016	J	`jnl`	Magging: Maximin Aggregation for Inhomogeneous Large-Scale Data. Proc. IEEE Peter Bühlmann, Nicolai Meinshausen
2015	J	`jnl`	Structural Intervention Distance for Evaluating Causal Graphs. Neural Comput. Jonas Peters, Peter Bühlmann
2014	J	`jnl`	High-dimensional learning of linear causal networks via inverse covariance estimation. J. Mach. Learn. Res. Po-Ling Loh, Peter Bühlmann
2014	J	`jnl`	High-dimensional variable screening and bias in subsequent inference, with an empirical comparison. Comput. Stat. Peter Bühlmann, Jacopo Mandozzi
2014	J	`jnl`	Hypersurfaces and Their Singularities in Partial Correlation Testing. Found. Comput. Math. Shaowei Lin, Caroline Uhler, Bernd Sturmfels, Peter Bühlmann
2014	J	`jnl`	Pattern alternating maximization algorithm for missing data in high-dimensional problems. J. Mach. Learn. Res. Nicolas Städler, Daniel J. Stekhoven, Peter Bühlmann
2014	J	`jnl`	Two optimal strategies for active learning of causal models from interventional data. Int. J. Approx. Reason. Alain Hauser, Peter Bühlmann
2013	J	`jnl`	CAM: Causal Additive Models, high-dimensional order search and penalized regression. CoRR Peter Bühlmann, Jonas Peters, Jan Ernest
2013	J	`jnl`	Causal statistical inference in high dimensions. Math. Methods Oper. Res. Peter Bühlmann
2013	J	`jnl`	Stable graphical model estimation with Random Forests for discrete, continuous, and mixed variables. Comput. Stat. Data Anal. Bernd Fellinghauer, Peter Bühlmann, Martin Ryffel, Michael von Rhein, Jan D. Reinhardt
2012	J	`jnl`	Causal stability ranking. Bioinform. Daniel J. Stekhoven, Izabel Moraes, Gardar Sveinbjörnsson, Lars Hennig, Marloes H. Maathuis, Peter Bühlmann
2012	J	`jnl`	Characterization and greedy learning of interventional Markov equivalence classes of directed acyclic graphs. J. Mach. Learn. Res. Alain Hauser, Peter Bühlmann
2012	J	`jnl`	MissForest - non-parametric missing value imputation for mixed-type data. Bioinform. Daniel J. Stekhoven, Peter Bühlmann
2012	J	`jnl`	Missing values: sparse inverse covariance estimation and an extension to sparse regression. Stat. Comput. Nicolas Städler, Peter Bühlmann
2012	J	`jnl`	Two Optimal Strategies for Active Learning of Causal Models from Interventions CoRR Alain Hauser, Peter Bühlmann
2011	J	`jnl`	Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs CoRR Alain Hauser, Peter Bühlmann
2011	A	`conf`	Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs (Abstract). UAI Alain Hauser, Peter Bühlmann
2011	J	`jnl`	High-dimensional Covariance Estimation Based On Gaussian Graphical Models. J. Mach. Learn. Res. Shuheng Zhou, Philipp Rütimann, Min Xu, Peter Bühlmann
2010	J	`jnl`	Model-based Boosting 2.0. J. Mach. Learn. Res. Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner
2010	J	`jnl`	Twin Boosting: improved feature selection and prediction. Stat. Comput. Peter Bühlmann, Torsten Hothorn
2008	J	`jnl`	Annotating novel genes by integrating synthetic lethals and genomic information. BMC Syst. Biol. Daniel Schöner, Markus Kalisch, Christian Leisner, Lukas Meier, Marc Sohrmann, Mahamadou Faty, Yves Barral, Matthias Peter, Wilhelm Gruissem, Peter Bühlmann
2008	J	`jnl`	Robustified L Comput. Stat. Data Anal. Roman Werner Lutz, Markus Kalisch, Peter Bühlmann
2007	J	`jnl`	Analyzing gene expression data in terms of gene sets: methodological issues. Bioinform. Jelle J. Goeman, Peter Bühlmann
2007	J	`jnl`	Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm. J. Mach. Learn. Res. Markus Kalisch, Peter Bühlmann
2007	J	`jnl`	Penalized likelihood for sparse contingency tables with an application to full-length cDNA libraries. BMC Bioinform. Corinne Dahinden, Giovanni Parmigiani, Mark C. Emerick, Peter Bühlmann
2006	J	`jnl`	A systematic comparison and evaluation of biclustering methods for gene expression data. Bioinform. Amela Prelic, Stefan Bleuler, Philip Zimmermann, Anja Wille, Peter Bühlmann, Wilhelm Gruissem, Lars Hennig, Lothar Thiele, Eckart Zitzler
2006	J	`jnl`	Model-based boosting in high dimensions. Bioinform. Torsten Hothorn, Peter Bühlmann
2006	J	`jnl`	Sparse Boosting. J. Mach. Learn. Res. Peter Bühlmann, Bin Yu
2005	—	`conf`	Boosting and l GfKl Peter Bühlmann
2003	J	`jnl`	Boosting for Tumor Classification with Gene Expression Data. Bioinform. Marcel Dettling, Peter Bühlmann