Andreas Gerhardus

According to our database, Andreas Gerhardus authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support.

Martin Rabel, Wiebke Günther, Jakob Runge, Andreas Gerhardus

CoRR, 2024

Leveraging Causal Information for Multivariate Timeseries Anomaly Detection.

Lukas Heppel, Andreas Gerhardus, Ferdinand Rewicki, Jan Christian Deeken, Günther Waxenegger-Wilfing

Proceedings of the 35th International Conference on Principles of Diagnosis and Resilient Systems, 2024

Bootstrap aggregation and confidence measures to improve time series causal discovery.

Kevin Debeire, Andreas Gerhardus, Jakob Runge, Veronika Eyring

Proceedings of the Causal Learning and Reasoning, 2024

2023

Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation.

Oana-Iuliana Popescu, Andreas Gerhardus, Jakob Runge

CoRR, 2023

Projecting infinite time series graphs to finite marginal graphs using number theory.

Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge

CoRR, 2023

Discovering Causal Relations and Equations from Data.

Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad, Gherardo Varando, Georg Martius, Emili Balaguer-Ballester, Ricardo Vinuesa, Emiliano Diaz, Laure Zanna, Jakob Runge

CoRR, 2023

Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery.

Saranya Ganesh S., Tom Beucler, Frederick Iat-Hin Tam, Milton S. Gomez, Jakob Runge, Andreas Gerhardus

CoRR, 2023

Increasing effect sizes of pairwise conditional independence tests between random vectors.

Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2021

Characterization of causal ancestral graphs for time series with latent confounders.

Andreas Gerhardus

CoRR, 2021

2020

High-recall causal discovery for autocorrelated time series with latent confounders.

Andreas Gerhardus, Jakob Runge

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020