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Enhancing the sensitivity to dark matter signatures in the very-high-energy gamma-ray band through machine learning Nieto, Daniel
Item Metadata
| Title |
Enhancing the sensitivity to dark matter signatures in the very-high-energy gamma-ray band through machine learning
|
| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
|
| Date Issued |
2018-02-28T11:14
|
| Extent |
41 minutes
|
| Subject | |
| Type | |
| File Format |
video/mp4
|
| Language |
eng
|
| Notes |
Author affiliation: Universidad Complutense de Madrid
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| Series | |
| Date Available |
2018-08-27
|
| Provider |
Vancouver : University of British Columbia Library
|
| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
|
| DOI |
10.14288/1.0371263
|
| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
|
| Scholarly Level |
Postdoctoral
|
| Rights URI | |
| Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International