Search Results for author: Mateo Espinosa Zarlenga

Found 2 papers, 1 papers with code

Efficient Decompositional Rule Extraction for Deep Neural Networks

1 code implementation24 Nov 2021 Mateo Espinosa Zarlenga, Zohreh Shams, Mateja Jamnik

In recent years, there has been significant work on increasing both interpretability and debuggability of a Deep Neural Network (DNN) by extracting a rule-based model that approximates its decision boundary.

On The Quality Assurance Of Concept-Based Representations

no code implementations29 Sep 2021 Mateo Espinosa Zarlenga, Pietro Barbiero, Zohreh Shams, Dmitry Kazhdan, Umang Bhatt, Mateja Jamnik

Recent work on Explainable AI has focused on concept-based explanations, where deep learning models are explained in terms of high-level units of information, referred to as concepts.

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