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stat.ME2026
Cost-Aware Optimized Front-Door Experimental Design
Leopold Mareis, Mathias Drton
Causal effect estimation often succeeds cost-constrained sequential data collection. This work considers multivariate linear front-door models with arbitrary unobserved confounding…
stat.ME2024
Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity
David Strieder, Mathias Drton
A fundamental challenge of scientific research is inferring causal relations based on observed data. One commonly used approach involves utilizing structural causal models that pos…
stat.ME2024
Dual Likelihood for Causal Inference under Structure Uncertainty
David Strieder, Mathias Drton
Knowledge of the underlying causal relations is essential for inferring the effect of interventions in complex systems. In a widely studied approach, structural causal models postu…