Anomaly-aware summary statistic from data batches
Signal-agnostic data exploration based on machine learning could unveil very subtle statistical deviations of collider data from the expected Standard Model of particle physics. The beneficial impact of a large training sample on machine learning solutions motivates the exploration of increasingly l...
Main Author: | Grosso, G. |
---|---|
Other Authors: | Massachusetts Institute of Technology. Laboratory for Nuclear Science |
Format: | Article |
Language: | English |
Published: |
Springer Berlin Heidelberg
2024
|
Online Access: | https://hdl.handle.net/1721.1/157890 |
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