Jakob Runge

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 34

Top Topics

Confidence Measures

Conditional Independence

Models With Hidden Variables

Causal Discovery

Top Venues

Publications

Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CLeaR (2024)
Kevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring
Bootstrap aggregation and confidence measures to improve time series causal discovery. CLeaR (2024)
Jonas Wahl, Urmi Ninad, Jakob Runge
Vector Causal Inference between Two Groups of Variables. AAAI (2023)
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 (2023)
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 (2023)
Wiebke Günther, Urmi Ninad, Jakob Runge
Causal Discovery for time series from multiple datasets with latent contexts. UAI (2023)
Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge
Increasing effect sizes of pairwise conditional independence tests between random vectors. UAI (2023)
Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge
Projecting infinite time series graphs to finite marginal graphs using number theory. CoRR (2023)
Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge
Invariance & Causal Representation Learning: Prospects and Limitations. CoRR (2023)
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)
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 (2023)
Oana-Iuliana Popescu, Andreas Gerhardus, Jakob Runge
Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation. CoRR (2023)
Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions. CoRR (2023)
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 (2023)
Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery. NeurIPS (2022)
Jakob Runge
Necessary and sufficient conditions for optimal adjustment sets in causal graphical models with hidden variables. CoRR (2021)
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)
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)
Jakob Runge
Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables. NeurIPS (2021)
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 (2021)
Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler
Conditional Adversarial Debiasing: Towards Learning Unbiased Classifiers from Biased Data. GCPR (2021)
Christian Reimers, Paul Bodesheim, Jakob Runge, Joachim Denzler
Towards Learning an Unbiased Classifier from Biased Data via Conditional Adversarial Debiasing. CoRR (2021)
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 (2021)
Jakob Runge
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. UAI (2020)
Christian Reimers, Jakob Runge, Joachim Denzler
Determining the Relevance of Features for Deep Neural Networks. ECCV (26) (2020)
Jakob Runge
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets. CoRR (2020)
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 (2020)
Gustau Camps-Valls, Dino Sejdinovic, Jakob Runge, Markus Reichstein
A Perspective on Gaussian Processes for Earth Observation. CoRR (2020)
Andreas Gerhardus, Jakob Runge
High-recall causal discovery for autocorrelated time series with latent confounders. NeurIPS (2020)
Andreas Gerhardus, Jakob Runge
High-recall causal discovery for autocorrelated time series with latent confounders. CoRR (2020)
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)
Jakob Runge, Xavier-Andoni Tibau, Matthias Bruhns, Jordi Muñoz-Marí, Gustau Camps-Valls
The Causality for Climate Competition. NeurIPS (Competition and Demos) (2019)
Jakob Runge
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. AISTATS (2018)
Jakob Runge
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. CoRR (2017)
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) (2013)
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) (2013)
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 (2012)