bivariate causal inference 1causal discovery 1likelihood estimation 1location-scale noise models 1skewed noise 1
From the 1 of 2 linked papers with an AI index.
2 papers
stat.ML2026
Skewness-Robust Causal Discovery in Location-Scale Noise Models
Daniel Klippert, Alexander Marx
The paper introduces SkewD, a likelihood‑based method for bivariate causal discovery that works with location‑scale noise models even when the noise distribution is skewed, improvi…
stat.AP2026
A Guide to Estimating Conditional Average Treatment Effects in Competing Risks Settings
Daniel Klippert, Sarah Friedrich, Markus Pauly
Conditional average treatment effects (CATEs) are central to treatment decision-making in personalized medicine. In competing risks settings, estimating CATEs from survival data al…