From the 1 of 5 linked papers with an AI index.
3 papers · 1 filter
Falsifying Causal Graphs With Outlier Events
William Roy Orchard, Philipp M. Faller, Dominik Janzing
The paper introduces statistical tests that use the propagation of outlier events to falsify candidate causal graphs, providing guarantees on false positives and detection power ev…
Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Francesco Montagna, Philipp M. Faller, Patrick Bloebaum +2
Causal discovery from observational data holds great promise, but existing methods rely on strong assumptions about the underlying causal structure, often requiring full observabil…
Cross-validating causal discovery via Leave-One-Variable-Out
Daniela Schkoda, Philipp Faller, Patrick Blöbaum +2
We propose a new approach to falsify causal discovery algorithms without ground truth, which is based on testing the causal model on a variable pair excluded during learning the ca…