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Julia Herbinger

4 accepted papers

2026

Functional Decomposition and Shapley Interactions for Interpreting Survival Models

Sophie Hanna Langbein, Hubert Baniecki, Fabian Fumagalli, Niklas Koenen, Marvin N. Wright, Julia Herbinger
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 0Source ↗Scholar ↗
2025

Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory

Fabian Fumagalli, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer, Julia Herbinger
AISTATS 2025poster

Feature-based explanations, using perturbations or gradients, are a prevalent tool to understand decisions of black box machine learning models. Yet, differences between these methods still remain mostly unknown, which limits their applicability for practitioners. In this work, we introduce a unifie…

Cited by 0Source ↗code ↗Scholar ↗
2022

REPID: Regional Effect Plots with implicit Interaction Detection

Julia Herbinger, Bernd Bischl, Giuseppe Casalicchio
AISTATS 2022poster

Machine learning models can automatically learn complex relationships, such as non-linear and interaction effects. Interpretable machine learning methods such as partial dependence plots visualize marginal feature effects but may lead to misleading interpretations when feature interactions are prese…

Cited by 20Source ↗PDF ↗code ↗Scholar ↗
2021

Explaining Hyperparameter Optimization via Partial Dependence Plots

Julia Moosbauer, Julia Herbinger, Giuseppe Casalicchio, Marius Lindauer, Bernd Bischl
NeurIPS 2021poster

Automated hyperparameter optimization (HPO) can support practitioners to obtain peak performance in machine learning models. However, there is often a lack of valuable insights into the effects of different hyperparameters on the final model performance. This lack of explainability makes it difficul…

Cited by 85Source ↗PDF ↗code ↗Scholar ↗