3 papers
hep-ex2025
Anomaly preserving contrastive neural embeddings for end-to-end model-independent searches at the LHC
Kyle Metzger, Lana Xu, Mia Sodini +4
Anomaly detection - identifying deviations from Standard Model predictions - is a key challenge at the Large Hadron Collider due to the size and complexity of its datasets. This is…
hep-ex2024
Ultrafast jet classification on FPGAs for the HL-LHC
Patrick Odagiu, Zhiqiang Que, Javier Duarte +13
Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate array device. In this context, w…
physics.data-an2023
Machine Learning for Anomaly Detection in Particle Physics
Vasilis Belis, Patrick Odagiu, Thea Klæboe Årrestad
The detection of out-of-distribution data points is a common task in particle physics. It is used for monitoring complex particle detectors or for identifying rare and unexpected e…