55 citations · 58 across the 7 of their papers we have counts for
3 papers · 1 filter
Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation
Oana-Iuliana Popescu, Andreas Gerhardus, Jakob Runge
Conditional independence testing (CIT) is a common task in machine learning, e.g., for variable selection, and a main component of constraint-based causal discovery. While most cur…
Projecting infinite time series graphs to finite marginal graphs using number theory
Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher +2
In recent years, a growing number of method and application works have adapted and applied the causal-graphical-model framework to time series data. Many of these works employ time…
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls, Andreas Gerhardus, Urmi Ninad +7
Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur and to make testable models that explain the p…