Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Springer International Publishing
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Timeline
Mendeley readers
| Chapter title |
Gradient-Based Attribution Methods
|
|---|---|
| Chapter number | 9 |
| Book title |
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
|
| Published by |
Springer, Cham, September 2019
|
| DOI | 10.1007/978-3-030-28954-6_9 |
| Book ISBNs |
978-3-03-028953-9, 978-3-03-028954-6
|
| Authors |
Marco Ancona, Enea Ceolini, Cengiz Öztireli, Markus Gross |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 78 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 16 | 21% |
| Researcher | 11 | 14% |
| Student > Ph. D. Student | 7 | 9% |
| Student > Bachelor | 5 | 6% |
| Student > Doctoral Student | 2 | 3% |
| Other | 8 | 10% |
| Unknown | 29 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 26 | 33% |
| Biochemistry, Genetics and Molecular Biology | 5 | 6% |
| Social Sciences | 3 | 4% |
| Engineering | 3 | 4% |
| Business, Management and Accounting | 2 | 3% |
| Other | 8 | 10% |
| Unknown | 31 | 40% |