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Mendeley readers
Chapter title |
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial Networks
|
---|---|
Chapter number | 56 |
Book title |
Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series
|
Published by |
Springer, Cham, September 2019
|
DOI | 10.1007/978-3-030-30490-4_56 |
Book ISBNs |
978-3-03-030489-8, 978-3-03-030490-4
|
Authors |
Dan Li, Dacheng Chen, Baihong Jin, Lei Shi, Jonathan Goh, See-Kiong Ng, Li, Dan, Chen, Dacheng, Jin, Baihong, Shi, Lei, Goh, Jonathan, Ng, See-Kiong |
Mendeley readers
The data shown below were compiled from readership statistics for 691 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 691 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 136 | 20% |
Student > Master | 101 | 15% |
Researcher | 55 | 8% |
Student > Bachelor | 37 | 5% |
Other | 29 | 4% |
Other | 76 | 11% |
Unknown | 257 | 37% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 256 | 37% |
Engineering | 96 | 14% |
Mathematics | 7 | 1% |
Physics and Astronomy | 6 | <1% |
Economics, Econometrics and Finance | 5 | <1% |
Other | 34 | 5% |
Unknown | 287 | 42% |