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Characterizing machine learning’s capabilities to detect long duration transient gravitational- wave signals from isolated neutron stars
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| Document type | Communication à un colloque (Conference Paper) – Conférence invitée / Keynote |
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| Publication date | 2019 |
| Language | Anglais |
| Conference | "Congrès des doctorants", Paris, France (du 25/03/2019 au 29/03/2019) |
| Affiliation | UCL - SSH/IACS - Institute of Analysis of Change in Contemporary and Historical Societies |
| Links |
| Bibliographic reference | Miller, Andrew ; et. al. Characterizing machine learning’s capabilities to detect long duration transient gravitational- wave signals from isolated neutron stars.Congrès des doctorants (Paris, France, du 25/03/2019 au 29/03/2019). |
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| Permanent URL | http://hdl.handle.net/2078.1/256622 |