Publications

See Google Scholar or Research Gate for a full list of Jakob Runge’s publications. Selected recent publications of the group:

Runge, J. “Necessary and sufficient graphical conditions for optimal adjustment sets in causal graphical models with hidden variables” Advances in Neural Information Processing Systems 34 (NeurIPS 2021)
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Reimers, C., J. Runge, and J. Denzler. “Determining the Relevance of Features for Deep Neural Networks” European Conference on Computer Vision ECCV (2020)
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Runge, J. “Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets” Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence, UAI (2020).
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Nowack, P., J. Runge, V. Eyring, J.D. Haigh, “Causal networks for climate model evaluation and constrained projections”. Nature Communications 11: 1415 (2020).
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Runge, J., P. Nowack, M. Kretschmer, S. Flaxman, D. Sejdinovic, “Detecting and quantifying causal associations in large nonlinear time series datasets”. Science Advances 5, eaau4996 (2019).
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Runge, J., S. Bathiany, E. Bollt, G. Camps-Valls, D. Coumou, E. Deyle, C. Glymour, et al. “Inferring Causation from Time Series in Earth System Sciences.” Nature Communications 10: 2553 (2019).
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VT Trifunov, M Shadaydeh, J Runge, V Eyring, M Reichstein, J Denzler. Nonlinear causal link estimation under hidden confounding with an application to time series anomaly detection. German Conference on Pattern Recognition, 261-273 (2019)

Tibau, X., C. Requena-Mesa, C. Reimers, J. Denzler, V. Eyring, M. Reichstein, and J. Runge. 2018. “SupernoVAE : VAE Based Kernel PCA for Analysis of Spatio-Temporal Earth Data.” in Proceedings of the 8th International Workshop on Climate Informatics (2018), 1–4.

Runge, J. Causal network reconstruction from time series: From theoretical assumptions to practical estimation. Chaos An Interdiscip. J. Nonlinear Sci. 28, 075310 (2018).
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Runge, J. Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information. in Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (2018).
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