Kavli Affiliate: Mihoko M. Nojiri
| First 5 Authors: A. Hammad, Mihoko M Nojiri, , ,
| Summary:
In this article, we review recent machine learning methods used in
challenging particle identification of heavy-boosted particles at high-energy
colliders. Our primary focus is on attention-based Transformer networks. We
report the performance of state-of-the-art deep learning networks and further
improvement coming from the modification of networks based on physics insights.
Additionally, we discuss interpretable methods to understand network
decision-making, which are crucial when employing highly complex and deep
networks.
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