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Learning Interpretable Queries for Explainable Image Classification with Information Pursuit

Information Pursuit (IP) is an explainable prediction algorithm that greedily selects a sequence of interpretable queries about the data in order of information gain, updating its posterior at each step based on observed query-answer pairs.

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Cite this as

Stefan Kolek, Aditya Chattopadhyay, Kwan Ho Ryan Chan, Hector Andrade-Loarca, Gitta Kutyniok, Ren´e Vidal (2024). Dataset: Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. https://doi.org/10.57702/4m38jdk3

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Additional Info

Field	Value
Created	December 3, 2024
Last update	December 3, 2024
Defined In	https://doi.org/10.48550/arXiv.2312.11548
Author	Stefan Kolek
More Authors	Aditya Chattopadhyay Kwan Ho Ryan Chan Hector Andrade-Loarca Gitta Kutyniok Ren´e Vidal