Runge, Jakob

23 publications

CLeaR 2025 Non-Parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation Oana-Iuliana Popescu, Andreas Gerhardus, Martin Rabel, Jakob Runge

ICML 2025 Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella, Simon Bing, Jakob Runge

AISTATS 2025 Separation-Based Distance Measures for Causal Graphs Jonas Wahl, Jakob Runge

CLeaR 2025 Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery Rebecca J. Herman, Jonas Wahl, Urmi Ninad, Jakob Runge

UAI 2024 A Global Markov Property for Solutions of Stochastic Difference Equations and the Corresponding Full Time Graphs Tom Hochsprung, Jakob Runge, Andreas Gerhardus

CLeaR 2024 Bootstrap Aggregation and Confidence Measures to Improve Time Series Causal Discovery Kevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring

NeurIPS 2024 Causal Discovery with Endogenous Context Variables Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge

CLeaR 2024 Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge

TMLR 2024 Invariance & Causal Representation Learning: Prospects and Limitations Simon Bing, Tom Hochsprung, Jonas Wahl, Urmi Ninad, Jakob Runge

UAI 2023 Causal Discovery for Time Series from Multiple Datasets with Latent Contexts Wiebke Günther, Urmi Ninad, Jakob Runge

NeurIPS 2023 ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning Julia Kaltenborn, Charlotte Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick

JMLR 2023 Distinguishing Cause and Effect in Bivariate Structural Causal Models: A Systematic Investigation Christoph Käding, Jakob Runge

UAI 2023 Increasing Effect Sizes of Pairwise Conditional Independence Tests Between Random Vectors Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge

NeurIPSW 2023 Invariance & Causal Representation Learning: Prospects and Limitations Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge

AAAI 2023 Vector Causal Inference Between Two Groups of Variables Jonas Wahl, Urmi Ninad, Jakob Runge

NeurIPS 2022 Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge

CVPRW 2021 Conditional Dependence Tests Reveal the Usage of ABCD Rule Features and Bias Variables in Automatic Skin Lesion Classification Christian Reimers, Niklas Penzel, Paul Bodesheim, Jakob Runge, Joachim Denzler

CVPRW 2021 EarthNet2021: A Large-Scale Dataset and Challenge for Earth Surface Forecasting as a Guided Video Prediction Task Christian Requena-Mesa, Vitus Benson, Markus Reichstein, Jakob Runge, Joachim Denzler

NeurIPS 2021 Necessary and Sufficient Graphical Conditions for Optimal Adjustment Sets in Causal Graphical Models with Hidden Variables Jakob Runge

ECCV 2020 Determining the Relevance of Features for Deep Neural Networks Christian Reimers, Jakob Runge, Joachim Denzler

UAI 2020 Discovering Contemporaneous and Lagged Causal Relations in Autocorrelated Nonlinear Time Series Datasets Jakob Runge

NeurIPS 2020 High-Recall Causal Discovery for Autocorrelated Time Series with Latent Confounders Andreas Gerhardus, Jakob Runge

AISTATS 2018 Conditional Independence Testing Based on a Nearest-Neighbor Estimator of Conditional Mutual Information Jakob Runge