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Sophie Hanna Langbein

2 accepted papers

2026

Functional Decomposition and Shapley Interactions for Interpreting Survival Models

ICML 2026poster

Hazard and survival functions are natural, interpretable targets in time-to-event prediction, but their inherent non-additivity fundamentally limits standard additive explanation methods. We introduce Survival Functional Decomposition (SurvFD), a principled approach for analyzing feature interaction…

Cited by 0SourceScholar
2025

Gradient-based Explanations for Deep Learning Survival Models

ICML 2025poster

Deep learning survival models often outperform classical methods in time-to-event predictions, particularly in personalized medicine, but their "black box" nature hinders broader adoption. We propose a framework for gradient-based explanation methods tailored to survival neural networks, extending t…

Cited by 0SourcePDFScholar