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About Explaining Deep Neural Network (2022)
This document provides a survey of global interpretation methods for explaining deep neural networks. It begins with an introduction explaining the importance of interpretability in deep learning models. The document then reviews different terminology used in explainable artificial intelligence before providing a taxonomy of global interpretation methods. It evaluates the strengths and weaknesses of these methods and assesses challenges to their practical implementation. The paper concludes by discussing future research directions to address challenges in global interpretability.
Detailed Information
| Author: | ['Harre Bams Ayma Aranda'] |
|---|---|
| Publication Year: | 2023 |
| Pages: | 16 |
| Language: | English |
| Format: | |
| Price: | FREE |
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