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stat.ML2026
Representation Learning for Semiparametric Causal Mediation Analysis under No Essential Heterogeneity
Roberto Faleh, Sofia Morelli, Holger Brandt
We propose a two-stage estimator for structural mediation parameters that combines deep representation learning with G-estimation under the "no essential heterogeneity" (NEH) assum…
stat.ML2025
Advantages and limitations in the use of transfer learning for individual treatment effects in causal machine learning
Seyda Betul Aydin, Holger Brandt
Generalizing causal knowledge across diverse environments is challenging, especially when estimates from large-scale datasets must be applied to smaller or systematically different…