default search action
Jakob Runge
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c17]Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge:
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CLeaR 2024: 843-867 - [c16]Kevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring:
Bootstrap aggregation and confidence measures to improve time series causal discovery. CLeaR 2024: 979-1007 - [i19]Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick:
Causal Representation Learning in Temporal Data via Single-Parent Decoding. CoRR abs/2410.07013 (2024) - [i18]Martin Rabel, Wiebke Günther, Jakob Runge, Andreas Gerhardus:
Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support. CoRR abs/2410.20405 (2024) - 2023
- [j4]Christoph Käding, Jakob Runge:
Distinguishing Cause and Effect in Bivariate Structural Causal Models: A Systematic Investigation. J. Mach. Learn. Res. 24: 278:1-278:144 (2023) - [c15]Jonas Wahl, Urmi Ninad, Jakob Runge:
Vector Causal Inference between Two Groups of Variables. AAAI 2023: 12305-12312 - [c14]Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick:
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. NeurIPS 2023 - [c13]Wiebke Günther, Urmi Ninad, Jakob Runge:
Causal Discovery for time series from multiple datasets with latent contexts. UAI 2023: 766-776 - [c12]Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge:
Increasing effect sizes of pairwise conditional independence tests between random vectors. UAI 2023: 879-889 - [i17]Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam, Milton S. Gomez, Jakob Runge, Andreas Gerhardus:
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery. CoRR abs/2304.05294 (2023) - [i16]Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge:
Discovering Causal Relations and Equations from Data. CoRR abs/2305.13341 (2023) - [i15]Felix Wagner, Florian Nachtigall, Lukas Franken, Nikola Milojevic-Dupont, Rafael H. M. Pereira, Nicolas Koch, Jakob Runge, Marta Gonzalez, Felix Creutzig:
A Causal Discovery Approach To Learn How Urban Form Shapes Sustainable Mobility Across Continents. CoRR abs/2308.16599 (2023) - [i14]Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge:
Projecting infinite time series graphs to finite marginal graphs using number theory. CoRR abs/2310.05526 (2023) - [i13]Oana-Iuliana Popescu, Andreas Gerhardus, Jakob Runge:
Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation. CoRR abs/2310.11132 (2023) - [i12]Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge:
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CoRR abs/2311.02695 (2023) - [i11]Julia Kaltenborn, Charlotte E. E. Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick:
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning. CoRR abs/2311.03721 (2023) - [i10]Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge:
Invariance & Causal Representation Learning: Prospects and Limitations. CoRR abs/2312.03580 (2023) - 2022
- [c11]Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge:
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery. NeurIPS 2022 - 2021
- [j3]Violeta Teodora Trifunov, Maha Shadaydeh, Jakob Runge, Markus Reichstein, Joachim Denzler:
A Data-Driven Approach to Partitioning Net Ecosystem Exchange Using a Deep State Space Model. IEEE Access 9: 107873-107883 (2021) - [c10]Christian Requena-Mesa, Vitus Benson, Markus Reichstein, Jakob Runge, Joachim Denzler:
EarthNet2021: A Large-Scale Dataset and Challenge for Earth Surface Forecasting as a Guided Video Prediction Task. CVPR Workshops 2021: 1132-1142 - [c9]Christian Reimers, Niklas Penzel, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification. CVPR Workshops 2021: 1810-1819 - [c8]Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. GCPR 2021: 48-62 - [c7]Jakob Runge:
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables. NeurIPS 2021: 15762-15773 - [i9]Jakob Runge:
Necessary and sufficient conditions for optimal adjustment sets in causal graphical models with hidden variables. CoRR abs/2102.10324 (2021) - [i8]Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler:
Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing. CoRR abs/2103.06179 (2021) - [i7]Christian Requena-Mesa, Vitus Benson, Markus Reichstein, Jakob Runge, Joachim Denzler:
EarthNet2021: A large-scale dataset and challenge for Earth surface forecasting as a guided video prediction task. CoRR abs/2104.10066 (2021) - 2020
- [c6]Christian Reimers, Jakob Runge, Joachim Denzler:
Determining the Relevance of Features for Deep Neural Networks. ECCV (26) 2020: 330-346 - [c5]Andreas Gerhardus, Jakob Runge:
High-recall causal discovery for autocorrelated time series with latent confounders. NeurIPS 2020 - [c4]Jakob Runge:
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. UAI 2020: 1388-1397 - [i6]Jakob Runge:
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. CoRR abs/2003.03685 (2020) - [i5]Gustau Camps-Valls, Dino Sejdinovic, Jakob Runge, Markus Reichstein:
A Perspective on Gaussian Processes for Earth Observation. CoRR abs/2007.01238 (2020) - [i4]Andreas Gerhardus, Jakob Runge:
High-recall causal discovery for autocorrelated time series with latent confounders. CoRR abs/2007.01884 (2020) - [i3]Christian Requena-Mesa, Vitus Benson, Joachim Denzler, Jakob Runge, Markus Reichstein:
EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts. CoRR abs/2012.06246 (2020)
2010 – 2019
- 2019
- [c3]Violeta Teodora Trifunov, Maha Shadaydeh, Jakob Runge, Veronika Eyring, Markus Reichstein, Joachim Denzler:
Nonlinear Causal Link Estimation Under Hidden Confounding with an Application to Time Series Anomaly Detection. GCPR 2019: 261-273 - [c2]Jakob Runge, Xavier-Andoni Tibau, Matthias Bruhns, Jordi Muñoz-Marí, Gustau Camps-Valls:
The Causality for Climate Competition. NeurIPS (Competition and Demos) 2019: 110-120 - 2018
- [c1]Jakob Runge:
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. AISTATS 2018: 938-947 - 2017
- [i2]Jakob Runge:
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. CoRR abs/1709.01447 (2017) - 2013
- [j2]Jaroslav Hlinka, David Hartman, Martin Vejmelka, Jakob Runge, Norbert Marwan, Jürgen Kurths, Milan Palus:
Reliability of Inference of Directed Climate Networks Using Conditional Mutual Information. Entropy 15(6): 2023-2045 (2013) - [j1]Georgios Balasis, Reik V. Donner, Stelios M. Potirakis, Jakob Runge, Constantinos Papadimitriou, Ioannis A. Daglis, Konstantinos Eftaxias, Jürgen Kurths:
Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System. Entropy 15(11): 4844-4888 (2013) - 2012
- [i1]Jakob Runge, Jobst Heitzig, Norbert Marwan, Jürgen Kurths:
Quantifying Causal Coupling Strength: A Lag-specific Measure For Multivariate Time Series Related To Transfer Entropy. CoRR abs/1210.2748 (2012)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-01 01:09 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint