Variational Methods for Machine Learning with Applications to Deep Networks
Springer International Publishing
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Timeline
Mendeley readers
| Title |
Variational Methods for Machine Learning with Applications to Deep Networks
|
|---|---|
| Published by |
Springer International Publishing, January 2021
|
| DOI | 10.1007/978-3-030-70679-1 |
| ISBNs |
978-3-03-070678-4, 978-3-03-070679-1
|
| Authors |
Lucas Pinheiro Cinelli, Matheus Araújo Marins, Eduardo Antônio Barros da Silva, Sérgio Lima Netto, Cinelli, Lucas Pinheiro, Marins, Matheus Araújo, Barros da Silva, Eduardo Antônio, Netto, Sérgio Lima |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 37 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 14% |
| Student > Master | 5 | 14% |
| Researcher | 3 | 8% |
| Student > Bachelor | 1 | 3% |
| Professor | 1 | 3% |
| Other | 5 | 14% |
| Unknown | 17 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 6 | 16% |
| Computer Science | 5 | 14% |
| Physics and Astronomy | 4 | 11% |
| Mathematics | 2 | 5% |
| Linguistics | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 18 | 49% |