Semi-visible jets, energy-based models, and self-supervision
We present DarkCLR, a novel framework for detecting semi-visible jets at the LHC. DarkCLR uses a self-supervised contrastive-learning approach to create observables that are approximately invariant under relevant transformations. We use background-enhanced data to create a sensitive representation a...
Saved in:
Main Author: | Luigi Favaro, Michael Krämer, Tanmoy Modak, Tilman Plehn, Jan Rüschkamp |
---|---|
Format: | Article |
Language: | English |
Published: |
SciPost
2025-02-01
|
Series: | SciPost Physics |
Online Access: | https://scipost.org/SciPostPhys.18.2.042 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Semi-visible jets + X: illuminating dark showers with radiation
by: Bingxuan Liu, et al.
Published: (2024-12-01) -
Postprocessing of Accidental Scenarios by Semi-Supervised Self-Organizing Maps
by: Francesco Di Maio, et al.
Published: (2017-01-01) -
A Semi-Supervised Attention Model for Identifying Authentic Sneakers
by: Yang Yang, et al.
Published: (2020-03-01) -
Enhancing Semi-Supervised Learning With Concept Drift Detection and Self-Training: A Study on Classifier Diversity and Performance
by: Jose L. M. Perez, et al.
Published: (2025-01-01) -
Semi-supervised tri-Adaboost algorithm for network intrusion detection
by: Yali Yuan, et al.
Published: (2019-06-01)