Classification without labels: learning from mixed samples in high energy physics
Modern machine learning techniques can be used to construct powerful models for difficult collider physics problems. In many applications, however, these models are trained on imperfect simulations due to a lack of truth-level information in the data, which risks the model learning artifacts of the...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing AG
2018
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| Online Access: | http://hdl.handle.net/1721.1/114621 https://orcid.org/0000-0002-2406-8160 |