Interpretability in Deep Learning
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 compute...
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| Main Authors: | Somani, Ayush (Author), Horsch, Alexander (Author), Prasad, Dilip K. (Author) |
|---|---|
| Autor Corporativo: | SpringerLink (Online service) |
| Formato: | Electrónico eBook |
| Idioma: | inglés |
| Publicado: |
Cham :
Springer International Publishing : Imprint: Springer,
2023.
|
| Edición: | 1st ed. 2023. |
| Subjects: | |
| Acceso en liña: | https://doi.org/10.1007/978-3-031-20639-9 |
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