Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Springer International Publishing
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Timeline
Mendeley readers
| Chapter title |
The (Un)reliability of Saliency Methods
|
|---|---|
| Chapter number | 14 |
| Book title |
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
|
| Published by |
Springer, Cham, September 2019
|
| DOI | 10.1007/978-3-030-28954-6_14 |
| Book ISBNs |
978-3-03-028953-9, 978-3-03-028954-6
|
| Authors |
Pieter-Jan Kindermans, Sara Hooker, Julius Adebayo, Maximilian Alber, Kristof T. Schütt, Sven Dähne, Dumitru Erhan, Been Kim |
Mendeley readers
The data shown below were compiled from readership statistics for 487 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 487 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 124 | 25% |
| Student > Master | 94 | 19% |
| Researcher | 67 | 14% |
| Student > Bachelor | 44 | 9% |
| Other | 16 | 3% |
| Other | 35 | 7% |
| Unknown | 107 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 231 | 47% |
| Engineering | 58 | 12% |
| Mathematics | 10 | 2% |
| Physics and Astronomy | 8 | 2% |
| Medicine and Dentistry | 7 | 1% |
| Other | 50 | 10% |
| Unknown | 123 | 25% |