Interpretability in Deep Learning

ISBN-13: 9783031206412 / Angielski / Miękka / 2024

Ayush Somani; Alexander Horsch; Dilip K. Prasad

Opis

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 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 recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition.