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stat.ML2026
Amortizing Causal Sensitivity Analysis via Prior Data-Fitted Networks
Emil Javurek, Dennis Frauen, Marie Brockschmidt +2
Causal sensitivity analysis aims to provide bounds for causal effect estimates in the presence of unobserved confounding. However, existing methods for causal sensitivity analysis…
stat.ML2025
An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes
Emil Javurek, Valentyn Melnychuk, Jonas Schweisthal +3
Predicting individualized potential outcomes in sequential decision-making is central for optimizing therapeutic decisions in personalized medicine (e.g., which dosing sequence to…