Jakob Runge
Jakob Runge
Group Leader, Institute of Data Science, German Aerospace Center (DLR)
Bestätigte E-Mail-Adresse bei dlr.de - Startseite
Zitiert von
Zitiert von
Escaping the curse of dimensionality in estimating multivariate transfer entropy
J Runge, J Heitzig, V Petoukhov, J Kurths
Physical review letters 108 (25), 258701, 2012
Identifying causal gateways and mediators in complex spatio-temporal systems
J Runge, V Petoukhov, JF Donges, J Hlinka, N Jajcay, M Vejmelka, ...
Nature communications 6 (1), 1-10, 2015
Using causal effect networks to analyze different Arctic drivers of midlatitude winter circulation
M Kretschmer, D Coumou, JF Donges, J Runge
Journal of Climate 29 (11), 4069-4081, 2016
Quantifying causal coupling strength: A lag-specific measure for multivariate time series related to transfer entropy
J Runge, J Heitzig, N Marwan, J Kurths
Physical Review E 86 (6), 061121, 2012
Quantifying the strength and delay of climatic interactions: The ambiguities of cross correlation and a novel measure based on graphical models
J Runge, V Petoukhov, J Kurths
Journal of Climate 27 (2), 720-739, 2014
Momentary information transfer as a coupling measure of time series
B Pompe, J Runge
Physical Review E 83 (5), 051122, 2011
Disentangling different types of El Niño episodes by evolving climate network analysis
A Radebach, RV Donner, J Runge, JF Donges, J Kurths
Physical Review E 88 (5), 052807, 2013
Reliability of inference of directed climate networks using conditional mutual information
J Hlinka, D Hartman, M Vejmelka, J Runge, N Marwan, J Kurths, M Paluš
Entropy 15 (6), 2023-2045, 2013
Detecting and quantifying causal associations in large nonlinear time series datasets
J Runge, P Nowack, M Kretschmer, S Flaxman, D Sejdinovic
Science Advances 5 (11), eaau4996, 2019
Inferring causation from time series in Earth system sciences
J Runge, S Bathiany, E Bollt, G Camps-Valls, D Coumou, E Deyle, ...
Nature communications 10 (1), 1-13, 2019
Causal network reconstruction from time series: From theoretical assumptions to practical estimation
J Runge
Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (7), 075310, 2018
Turn down the heat: climate extremes, regional impacts, and the case for resilience.
HJ Schellnhuber, B Hare, O Serdeczny, M Schaeffer, S Adams, F Baarsch, ...
Turn down the heat: climate extremes, regional impacts, and the case for …, 2013
Statistical mechanics and information-theoretic perspectives on complexity in the earth system
G Balasis, RV Donner, SM Potirakis, J Runge, C Papadimitriou, IA Daglis, ...
Entropy 15 (11), 4844-4888, 2013
Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package
JF Donges, J Heitzig, B Beronov, M Wiedermann, J Runge, QY Feng, ...
Chaos: An Interdisciplinary Journal of Nonlinear Science 25 (11), 113101, 2015
Quantifying information transfer and mediation along causal pathways in complex systems
J Runge
Physical Review E 92 (6), 062829, 2015
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information
J Runge
Proceedings of the 21st International Conference on Artificial Intelligence …, 2018
Optimal model-free prediction from multivariate time series
J Runge, RV Donner, J Kurths
Physical Review E 91 (5), 052909, 2015
Early prediction of extreme stratospheric polar vortex states based on causal precursors
M Kretschmer, J Runge, D Coumou
Geophysical research letters 44 (16), 8592-8600, 2017
The role of the North Atlantic overturning and deep ocean for multi-decadal global-mean-temperature variability
CF Schleussner, J Runge, J Lehmann, A Levermann
Earth System Dynamics 5 (1), 103-115, 2014
Detecting and quantifying causality from time series of complex systems
J Runge
Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2014
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20