Titlebook: Interpretability in Deep Learning; Ayush Somani,Alexander Horsch,Dilip K. Prasad Book 2023 The Editor(s) (if applicable) and The Author(s)

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terpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition.. . . . .978-3-031-20641-2978-3-031-20639-9

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n the topic.Includes fuzzy deep learning architectures.This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures. In addition, it includes several case studies from

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Book 2023with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic. .The book can be used as a monograph on interpretability in deep learning covering the most rece

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978-3-031-20641-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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https://doi.org/10.1007/978-3-031-20639-9Interpretability; Deep Learning; Interpretable Learning; Neural Networks; Explainable Artificial Intelli

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Ayush Somani,Alexander Horsch,Dilip K. PrasadPresents full coverage of interpretability in deep learning.Explains the fundamental concepts of interpretability and the state of the art on the topic.Includes fuzzy deep learning architectures

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