Inherently Interpretable Machine Learning: A Contrasting Paradigm to Post-hoc Explainable AI
Crossref DOI link: https://doi.org/10.1007/s12599-025-00964-0
Published Online: 2025-09-15
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Zschech, Patrick
Weinzierl, Sven
Kraus, Mathias
Funding for this research was provided by:
Technische Universität Dresden
Text and Data Mining valid from 2025-09-15
Version of Record valid from 2025-09-15
Article History
Received: 17 December 2024
Accepted: 24 July 2025
First Online: 15 September 2025