Nicolai Meinshausen

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All published works

Action	Title	Year	Authors
+	PKLM: A FLEXIBLE MCAR TEST USING CLASSIFICATION	2025	Meta-Lina Spohn Jeffrey Näf Loris Michel Nicolai Meinshausen
+	Machine learning for exoplanet detection in high-contrast spectroscopy: Revealing exoplanets by leveraging hidden molecular signatures in cross-correlated spectra with convolutional neural networks	2024	Emily O. Garvin Markus J. Bonse Jean Hayoz Gabriele Cugno Jonas Spiller Polychronis Patapis D. J. M. Petit dit de la Roche Rakesh Nath-Ranga Olivier Absil Nicolai Meinshausen
+ PDF Chat	Machine Learning for Exoplanet Detection in High-Contrast Spectroscopy: Revealing Exoplanets by Leveraging Hidden Molecular Signatures in Cross-Correlated Spectra with Convolutional Neural Networks	2024	Emily O. Garvin Markus J. Bonse Jean Hayoz Gabriele Cugno Jonas Spiller Polychronis Patapis Dominique Roche Rakesh Nath-Ranga Olivier Absil Nicolai Meinshausen
+ PDF Chat	Distributional Principal Autoencoders	2024	Xinwei Shen Nicolai Meinshausen
+	Imputation scores	2023	Jeffrey Näf Meta-Lina Spohn Loris Michel Nicolai Meinshausen
+	Confidence and Uncertainty Assessment for Distributional Random Forests	2023	Jeffrey Näf Corinne Emmenegger Peter Bühlmann Nicolai Meinshausen
+	Engression: Extrapolation for Nonlinear Regression?	2023	Xinwei Shen Nicolai Meinshausen
+ PDF Chat	ricu: R’s interface to intensive care data	2022	Nicolas Bennett Drago Plečko Ida-Fong Ukor Nicolai Meinshausen Peter Bühlmann
+	Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions	2022	Andrew Jesson Alyson Douglas Peter Manshausen Nicolai Meinshausen Philip Stier Yarin Gal Uri Shalit
+	Robust detection and attribution of climate change under interventions	2022	Enikő Székely Sebastian Sippel Nicolai Meinshausen Guillaume Obozinski Reto Knutti
+	fairadapt: Causal Reasoning for Fair Data Pre-processing.	2021	Drago Plečko Nicolas Bennett Nicolai Meinshausen
+	Proper Scoring Rules for Missing Value Imputation	2021	Loris Michel Jeffrey Näf Meta-Lina Spohn Nicolai Meinshausen
+ PDF Chat	Causal discovery in heavy-tailed models	2021	Nicola Gnecco Nicolai Meinshausen Jonas Peters Sebastian Engelke
+ PDF Chat	Anchor Regression: Heterogeneous Data Meet Causality	2021	Dominik Rothenhäusler Nicolai Meinshausen Peter Bühlmann Jonas Peters
+	Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning	2021	Michael Moor Nicolas Bennett Drago Plečko Max Horn Bastian Rieck Nicolai Meinshausen Peter Bühlmann Karsten Borgwardt
+	fairadapt: Causal Reasoning for Fair Data Pre-processing	2021	Drago Plečko Nicolas Bennett Nicolai Meinshausen
+	PKLM: A flexible MCAR test using Classification	2021	Loris Michel Jeffrey Näf Meta-Lina Spohn Nicolai Meinshausen
+	Imputation Scores	2021	Jeffrey Näf Meta-Lina Spohn Loris Michel Nicolai Meinshausen
+	ricu: R's Interface to Intensive Care Data	2021	Nicolas Bennett Drago Plečko Ida-Fong Ukor Nicolai Meinshausen Peter Bühlmann
+ PDF Chat	Conditional variance penalties and domain shift robustness	2020	Christina Heinze‐Deml Nicolai Meinshausen
+	Spectral Deconfounding via Perturbed Sparse Linear Models	2020	Domagoj Ćevid Peter Bühlmann Nicolai Meinshausen
+	Fair Data Adaptation with Quantile Preservation	2020	Drago Plečko Nicolai Meinshausen
+	Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression.	2020	Domagoj Ćevid Loris Michel Nicolai Meinshausen Peter Bühlmann
+ PDF Chat	Right Singular Vector Projection Graphs: Fast High Dimensional Covariance Matrix Estimation under Latent Confounding	2020	Rajen D. Shah Benjamin Frot Gian-Andrea Thanei Nicolai Meinshausen
+	Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression	2020	Domagoj Ćevid Loris Michel Jeffrey Näf Nicolai Meinshausen Peter Bühlmann
+	High Probability Lower Bounds for the Total Variation Distance	2020	Loris Michel Jeffrey Näf Nicolai Meinshausen
+	Fair Data Adaptation with Quantile Preservation	2019	Drago Plečko Nicolai Meinshausen
+	Causal discovery in heavy-tailed models	2019	Nicola Gnecco Nicolai Meinshausen Jonas Peters Sebastian Engelke
+	Causal Dantzig: Fast inference in linear structural equation models with hidden variables under additive interventions	2019	Dominik Rothenhäusler Peter Bühlmann Nicolai Meinshausen
+	A direct approach to detection and attribution of climate change	2019	Enikő Székely Sebastian Sippel Reto Knutti Guillaume Obozinski Nicolai Meinshausen
+	Fair Data Adaptation with Quantile Preservation	2019	Drago Plečko Nicolai Meinshausen
+	Causal discovery in heavy-tailed models	2019	Nicola Gnecco Nicolai Meinshausen Jonas Peters Sebastian Engelke
+	RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding	2018	Rajen D. Shah Benjamin Frot Gian-Andrea Thanei Nicolai Meinshausen
+	Invariant Causal Prediction for Nonlinear Models	2018	Christina Heinze‐Deml Jonas Peters Nicolai Meinshausen
+	CAUSALITY FROM A DISTRIBUTIONAL ROBUSTNESS POINT OF VIEW	2018	Nicolai Meinshausen
+ PDF Chat	Symmetric rank covariances: a generalized framework for nonparametric measures of dependence	2018	Luca Weihs Mathias Drton Nicolai Meinshausen
+	Anchor regression: heterogeneous data meets causality	2018	Dominik Rothenhäusler Peter Bühlmann Nicolai Meinshausen Jonas Peters
+	Spectral Deconfounding via Perturbed Sparse Linear Models	2018	Domagoj Ćevid Peter Bühlmann Nicolai Meinshausen
+ PDF Chat	Preserving privacy between features in distributed estimation	2018	Christina Heinze‐Deml Brian McWilliams Nicolai Meinshausen
+	RSVP-graphs: Fast High-dimensional Covariance Matrix Estimation under Latent Confounding	2018	Rajen D. Shah Benjamin Frot Gian-Andrea Thanei Nicolai Meinshausen
+ PDF Chat	Causal Structure Learning	2017	Christina Heinze‐Deml Marloes H. Maathuis Nicolai Meinshausen
+	Guarding Against Adversarial Domain Shifts with Counterfactual Regularization.	2017	Christina Heinze‐Deml Nicolai Meinshausen
+	Invariant Causal Prediction for Nonlinear Models	2017	Christina Heinze‐Deml Jonas Peters Nicolai Meinshausen
+	Causal Dantzig: fast inference in linear structural equation models with hidden variables under additive interventions	2017	Dominik Rothenhäusler Peter Bühlmann Nicolai Meinshausen
+ PDF Chat	Random Projections for Large-Scale Regression	2017	Gian-Andrea Thanei Christina Heinze Nicolai Meinshausen
+	Symmetric Rank Covariances: a Generalised Framework for Nonparametric Measures of Dependence	2017	Luca Weihs Mathias Drton Nicolai Meinshausen
+	Causal Structure Learning	2017	Christina Heinze‐Deml Marloes H. Maathuis Nicolai Meinshausen
+	Random Projections For Large-Scale Regression	2017	Gian-Andrea Thanei Christina Heinze Nicolai Meinshausen
+	Causal Dantzig: fast inference in linear structural equation models with hidden variables under additive interventions	2017	Dominik Rothenhäusler Peter Bühlmann Nicolai Meinshausen
+	Conditional Variance Penalties and Domain Shift Robustness	2017	Christina Heinze‐Deml Nicolai Meinshausen
+	Invariant Causal Prediction for Nonlinear Models	2017	Christina Heinze‐Deml Jonas Peters Nicolai Meinshausen
+	The xyz algorithm for fast interaction search in high-dimensional data	2016	Gian-Andrea Thanei Nicolai Meinshausen Rajen D. Shah
+ PDF Chat	Causal Inference by using Invariant Prediction: Identification and Confidence Intervals	2016	Jonas Peters Peter Bühlmann Nicolai Meinshausen
+ PDF Chat	Confidence Intervals for Maximin Effects in Inhomogeneous Large-Scale Data	2016	Dominik Rothenhäusler Nicolai Meinshausen Peter Bühlmann
+ PDF Chat	Minimum Distance Lasso for robust high-dimensional regression	2016	Aurélie Lozano Nicolai Meinshausen Eunho Yang
+	Scalable Adaptive Stochastic Optimization Using Random Projections	2016	Gabriel Krummenacher Brian McWilliams Yannic Kilcher Joachim M. Buhmann Nicolai Meinshausen
+	Causal inference by using invariant prediction: identification and confidence intervals	2016	Jonas Peters Peter Bühlmann Nicolai Meinshausen
+	The xyz algorithm for fast interaction search in high-dimensional data	2016	Gian-Andrea Thanei Nicolai Meinshausen Rajen D. Shah
+ PDF Chat	Magging: Maximin Aggregation for Inhomogeneous Large-Scale Data	2015	Peter Bühlmann Nicolai Meinshausen
+	High-Dimensional Inference: Confidence Intervals, $p$-Values and R-Software hdi	2015	Ruben Dezeure Peter Bühlmann Lukas Meier Nicolai Meinshausen
+	Maximin effects in inhomogeneous large-scale data	2015	Nicolai Meinshausen Peter Bühlmann
+	DUAL-LOCO: Distributing Statistical Estimation Using Random Projections	2015	Christina Heinze Brian McWilliams Nicolai Meinshausen
+	Causal inference using invariant prediction: identification and confidence intervals	2015	Jonas Peters Peter Bühlmann Nicolai Meinshausen
+	DUAL-LOCO: Distributing Statistical Estimation Using Random Projections	2015	Christina Heinze Brian McWilliams Nicolai Meinshausen
+	backShift: Learning causal cyclic graphs from unknown shift interventions	2015	Dominik Rothenhäusler Christina Heinze Jonas Peters Nicolai Meinshausen
+	Confidence Intervals for Maximin Effects in Inhomogeneous Large-Scale Data	2015	Dominik Rothenhäusler Nicolai Meinshausen Peter Bühlmann
+	Causal inference using invariant prediction: identification and confidence intervals	2015	Jonas Peters Peter Bühlmann Nicolai Meinshausen
+ PDF Chat	Group Bound: Confidence Intervals for Groups of Variables in Sparse High Dimensional Regression Without Assumptions on the Design	2014	Nicolai Meinshausen
+	Magging: maximin aggregation for inhomogeneous large-scale data	2014	Peter Bühlmann Nicolai Meinshausen
+	LOCO: Distributing Ridge Regression with Random Projections	2014	Christina Heinze Brian McWilliams Nicolai Meinshausen Gabriel Krummenacher
+	Magging: maximin aggregation for inhomogeneous large-scale data	2014	Peter Bühlmann Nicolai Meinshausen
+	Assumption-free confidence intervals for groups of variables in sparse high-dimensional regression	2013	Nicolai Meinshausen
+	Group-bound: confidence intervals for groups of variables in sparse high-dimensional regression without assumptions on the design	2013	Nicolai Meinshausen
+	Min-wise hashing for large-scale regression and classication with sparse data	2013	Rajen D. Shah Nicolai Meinshausen
+	Minimum Distance Estimation for Robust High-Dimensional Regression	2013	Aurélie Lozano Nicolai Meinshausen
+	Random Intersection Trees	2013	Rajen D. Shah Nicolai Meinshausen
+	Discussion of Grouping Strategies and Thresholding for High Dimension Linear Models	2013	Nicolai Meinshausen
+	On b-bit min-wise hashing for large-scale regression and classification with sparse data	2013	Rajen D. Shah Nicolai Meinshausen
+ PDF Chat	Sign-constrained least squares estimation for high-dimensional regression	2013	Nicolai Meinshausen
+	Group-bound: confidence intervals for groups of variables in sparse high-dimensional regression without assumptions on the design	2013	Nicolai Meinshausen
+	Random Intersection Trees	2013	Rajen D. Shah Nicolai Meinshausen
+	Minimum Distance Estimation for Robust High-Dimensional Regression	2013	Aurélie Lozano Nicolai Meinshausen
+	Discussion: Latent variable graphical model selection via convex optimization	2012	Steffen L. Lauritzen Nicolai Meinshausen
+	Sign-constrained least squares estimation for high-dimensional regression	2012	Nicolai Meinshausen
+	Sign-constrained least squares estimation for high-dimensional regression	2012	Nicolai Meinshausen
+	Asymptotic optimality of the Westfall–Young permutation procedure for multiple testing under dependence	2011	Nicolai Meinshausen Marloes H. Maathuis Peter Bühlmann
+ PDF Chat	Discussion of “Multiple Testing for Exploratory Research” by J. J. Goeman and A. Solari	2011	Nicolai Meinshausen
+ PDF Chat	LASSO Isotone for High-Dimensional Additive Isotonic Regression	2011	Zhou Fang Nicolai Meinshausen
+	Optimality of the Westfall-Young permutation procedure for multiple testing under dependence	2011	Nicolai Meinshausen Marloes H. Maathuis
+ PDF Chat	Node harvest	2010	Nicolai Meinshausen
+ PDF Chat	Stability Selection	2010	Nicolai Meinshausen Peter Bühlmann
+	LASSO ISOtone for High Dimensional Additive Isotonic Regression	2010	Zhou Fang Nicolai Meinshausen
+ PDF Chat	<i>p</i>-Values for High-Dimensional Regression	2009	Nicolai Meinshausen Lukas Meier Peter Bühlmann
+	Node harvest: simple and interpretable regression and classication	2009	Nicolai Meinshausen
+ PDF Chat	Efficient blind search: Optimal power of detection under computational cost constraints	2009	Nicolai Meinshausen Peter J. Bickel John Rice
+ PDF Chat	Lasso-type recovery of sparse representations for high-dimensional data	2009	Nicolai Meinshausen Bin Yu
+ PDF Chat	Forest Garrote	2009	Nicolai Meinshausen
+	Forest Garrote	2009	Nicolai Meinshausen
+	Stability Selection	2008	Nicolai Meinshausen Peter Buehlmann
+ PDF Chat	Discussion of: Treelets—An adaptive multi-scale basis for sparse unordered data	2008	Nicolai Meinshausen Peter Bühlmann
+	Hierarchical testing of variable importance	2008	Nicolai Meinshausen
+	P-values for high-dimensional regression	2008	Nicolai Meinshausen Lukas Meier Peter Bühlmann
+	Discussion of: Treelets--An adaptive multi-scale basis for sparse unordered data	2008	Nicolai Meinshausen Peter Bühlmann
+	Stability Selection	2008	Nicolai Meinshausen Peter Buehlmann
+ PDF Chat	Discussion: A tale of three cousins: Lasso, L2Boosting and Dantzig	2007	Nicolai Meinshausen Guilherme V. Rocha Bin Yu
+	A note on the Lasso for Gaussian graphical model selection	2007	Nicolai Meinshausen
+	Relaxed Lasso	2006	Nicolai Meinshausen
+	Quantile Regression Forests	2006	Nicolai Meinshausen
+ PDF Chat	Search for small trans-Neptunian objects by the TAOS project	2006	W. P. Chen Charles Alcock T. S. Axelrod Federica Bianco Y.‐I. Byun Yuan Chang K. H. Cook R. Dave J. Giammarco D. W. Kim
+	High-dimensional graphs and variable selection with the Lasso	2006	Nicolai Meinshausen Peter Bühlmann
+ PDF Chat	Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses	2006	Nicolai Meinshausen John Rice
+	Testing for monotonicity in the Hubble diagram	2006	Nicolai Meinshausen John P. Rice Thomas Schücker
+	False Discovery Control for Multiple Tests of Association Under General Dependence	2005	Nicolai Meinshausen
+ PDF Chat	Lower bounds for the number of false null hypotheses for multiple testing of associations under general dependence structures	2005	Nicolai Meinshausen Peter Bühlmann
+	Lasso with relaxation	2005	Nicolai Meinshausen
+	Consistent neighbourhood selection for sparse high-dimensional graphs with the Lasso	2004	Nicolai Meinshausen Peter Bühlmann
+	Upper bounds for the number of true null hypotheses and novel estimates for error rates in multiple testing	2004	Nicolai Meinshausen Peter Bühlmann

Common Coauthors

Coauthor	Papers Together
Peter Bühlmann	34
Jonas Peters	13
Rajen D. Shah	9
Christina Heinze‐Deml	9
Drago Plečko	8
Dominik Rothenhäusler	8
Jeffrey Näf	8
Loris Michel	8
Gian-Andrea Thanei	7
Christina Heinze	6
Meta-Lina Spohn	5
Brian McWilliams	5
Nicolas Bennett	5
Marloes H. Maathuis	4
Domagoj Ćevid	4
Nicola Gnecco	3
Sebastian Engelke	3
John Rice	3
Aurélie Lozano	3
Lukas Meier	3
Benjamin Frot	3
Olivier Absil	2
Reto Knutti	2
Jean Hayoz	2
Mathias Drton	2
Sascha P. Quanz	2
Zhou Fang	2
Gabriel Krummenacher	2
Ida-Fong Ukor	2
Sebastian Sippel	2
Polychronis Patapis	2
Guillaume Obozinski	2
Luca Weihs	2
Peter Buehlmann	2
Jonas Spiller	2
Rakesh Nath-Ranga	2
Bin Yu	2
Markus J. Bonse	2
Emily O. Garvin	2
Enikő Székely	2
Gabriele Cugno	2
Philip Stier	1
John P. Rice	1
C. C. Lin	1
Y.‐I. Byun	1
S.‐K. King	1
K. H. Cook	1
H. C. Lin	1
S. Marshall	1
Dominique Roche	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	33
+ PDF Chat	Least angle regression	2004	Bradley Efron Trevor Hastie Iain M. Johnstone Robert Tibshirani	21
+	High-dimensional graphs and variable selection with the Lasso	2006	Nicolai Meinshausen Peter Bühlmann	15
+ PDF Chat	The Adaptive Lasso and Its Oracle Properties	2006	Hui Zou	13
+ PDF Chat	Model Selection and Estimation in Regression with Grouped Variables	2005	Ming Yuan Yi Lin	12
+ PDF Chat	Simultaneous analysis of Lasso and Dantzig selector	2009	Peter J. Bickel Ya’acov Ritov Alexandre B. Tsybakov	11
+	On Model Selection Consistency of Lasso	2006	Peng Zhao Bin Yu	10
+	Statistics for High-Dimensional Data: Methods, Theory and Applications	2011	Peter Bhlmann Sara van de Geer	9
+ PDF Chat	High-dimensional generalized linear models and the lasso	2008	Sara A. van de Geer	9
+ PDF Chat	Sure Independence Screening for Ultrahigh Dimensional Feature Space	2008	Jianqing Fan Jinchi Lv	9
+ PDF Chat	Causal Inference by using Invariant Prediction: Identification and Confidence Intervals	2016	Jonas Peters Peter Bühlmann Nicolai Meinshausen	8
+	A Simple Sequentially Rejective Multiple Test Procedure	1979	Sture Holm	8
+ PDF Chat	The sparsity and bias of the Lasso selection in high-dimensional linear regression	2008	Cun-Hui Zhang Jian Huang	8
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	8
+ PDF Chat	The Group Lasso for Logistic Regression	2008	Lukas Meier Sara van de Geer Peter Bühlmann	7
+	On the LASSO and Its Dual	2000	M. R. Osborne Brett Presnell Berwin A. Turlach	7
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	7
+ PDF Chat	Asymptotics for lasso-type estimators	2000	Wenjiang Fu Keith Knight	7
+ PDF Chat	The control of the false discovery rate in multiple testing under dependency	2001	Yoav Benjamini Daniel Yekutieli	7
+ PDF Chat	The Dantzig selector: Statistical estimation when p is much larger than n	2007	Emmanuel J. Candès Terence Tao	7
+ PDF Chat	Robust Regression: Asymptotics, Conjectures and Monte Carlo	1973	Peter J. Huber	7
+	Sharp thresholds for high-dimensional and noisy recovery of sparsity	2006	Martin J. Wainwright	6
+ PDF Chat	Jointly Interventional and Observational Data: Estimation of Interventional Markov Equivalence Classes of Directed Acyclic Graphs	2014	Alain Hauser Peter Bühlmann	6
+	Marginal Structural Models and Causal Inference in Epidemiology	2000	James M. Robins Miguel A. Hernán Babette Brumback	6
+	Model selection and estimation in the Gaussian graphical model	2007	Ming Yuan Yi Lin	6
+ PDF Chat	Pathwise coordinate optimization	2007	Jerome H. Friedman Trevor Hastie Holger Höfling Robert Tibshirani	6
+	The Elements of Statistical Learning	2001	Trevor Hastie J. Friedman Robert Tibshirani	6
+ PDF Chat	Statistical Methods for Detecting Stellar Occultations by Kuiper Belt Objects: The Taiwanese–American Occultation Survey	2004	Chyng-Lan Liang John A. Rice Imke de Pater Charles Alcock T. S. Axelrod J.-H. Wang Stuart Marshall	6
+	Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment.	1994	Michael A. Martin Peter H. Westfall S. Stanley Young	6
+ PDF Chat	Square-root lasso: pivotal recovery of sparse signals via conic programming	2011	Alexandre Belloni Victor Chernozhukov Lei Wang	5
+	Quantile Regression Forests	2006	Nicolai Meinshausen	5
+ PDF Chat	On the conditions used to prove oracle results for the Lasso	2009	Sara A. van de Geer Peter Bühlmann	5
+	Maximin effects in inhomogeneous large-scale data	2015	Nicolai Meinshausen Peter Bühlmann	5
+ PDF Chat	Estimating the proportion of false null hypotheses among a large number of independently tested hypotheses	2006	Nicolai Meinshausen John Rice	5
+	Causal Inference Using Potential Outcomes	2005	Donald B. Rubin	5
+ PDF Chat	Aggregation for Gaussian regression	2007	Florentina Bunea Alexandre B. Tsybakov Marten Wegkamp	5
+	Avoiding Discrimination through Causal Reasoning	2017	Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf	5
+	CAM: Causal additive models, high-dimensional order search and penalized regression	2014	Peter Bühlmann Jonas Peters Jan Ernest	5
+	CAUSALITY FROM A DISTRIBUTIONAL ROBUSTNESS POINT OF VIEW	2018	Nicolai Meinshausen	5
+	Persistence in high-dimensional linear predictor selection and the virtue of overparametrization	2004	Eitan Greenshtein Ya’acov Ritov	5
+	A NOTE ON THE LASSO AND RELATED PROCEDURES IN MODEL SELECTION	2006	Chenlei Leng Yi Lin Grace Wahba	5
+	Causal discovery with continuous additive noise models	2014	Jonas Peters Joris M. Mooij Dominik Janzing Bernhard Schölkopf	5
+ PDF Chat	Assumptions of IV Methods for Observational Epidemiology	2010	Vanessa Didelez Meng Sha Nuala A. Sheehan	5
+ PDF Chat	Sparsity oracle inequalities for the Lasso	2007	Florentina Bunea Alexandre B. Tsybakov Marten Wegkamp	5
+	Predictive learning via rule ensembles	2008	Jerome H. Friedman Bogdan Popescu	5
+ PDF Chat	Estimating high-dimensional intervention effects from observational data	2009	Marloes H. Maathuis Markus Kalisch Peter Bühlmann	5
+ PDF Chat	A characterization of Markov equivalence classes for acyclic digraphs	1997	Steen A. Andersson David Madigan Michael D. Perlman	5
+	Regularization Paths for Generalized Linear Models via Coordinate Descent.	2010	Jerome H. Friedman Trevor Hastie Rob Tibshirani	4
+ PDF Chat	A Non-Parametric Test of Independence	1948	Wassily Hoeffding	4
+ PDF Chat	Sparsity and Smoothness Via the Fused Lasso	2004	Robert Tibshirani Michael A. Saunders Saharon Rosset Ji Zhu Keith Knight	4