• Corpus ID: 238856899

Challenges for Unsupervised Anomaly Detection in Particle Physics

@article{Fraser2021ChallengesFU,
  title={Challenges for Unsupervised Anomaly Detection in Particle Physics},
  author={Katherine Fraser and Samuel Homiller and Rashmish K. Mishra and Bryan Ostdiek and Matthew D. Schwartz},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.06948}
}
Anomaly detection relies on designing a score to determine whether a particular event is uncharacteristic of a given background distribution. One way to define a score is to use autoencoders, which rely on the ability to reconstruct certain types of data (background) but not others (signals). In this paper, we study some challenges associated with variational autoencoders, such as the dependence on hyperparameters and the metric used, in the context of anomalous signal (top and W ) jets in a… 
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