49 citations · 348 across the 19 of their papers we have counts for
19 papers
Continual Learning via Ensemble-Based Depth-Wise Masked Autoencoders for Data Quality Monitoring in High-Energy Physics
Dale Julson, Eric Reinhardt, Andrii Krutsylo +5
Machine learning (ML) techniques have been demonstrated to improve the accuracy and efficiency of anomaly detection (AD) when compared to conventional methods. This has led to the…
Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter
Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang +12
The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data quality mon…
Autoencoder-based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter
The CMS ECAL Collaboration
The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online Data Quality Monitoring of the CMS electromagnetic calorimeter is a…
Report of the Topical Group on Higgs Physics for Snowmass 2021: The Case for Precision Higgs Physics
Sally Dawson, Patrick Meade, Isobel Ojalvo +78
A future Higgs Factory will provide improved precision on measurements of Higgs couplings beyond those obtained by the LHC, and will enable a broad range of investigations across t…
Four-top quark physics at the LHC
Freya Blekman, Fréderic Déliot, Valentina Dutta +1
The production of four top quarks is a rare process in the Standard Model that provides unique opportunities and sensitivity to Standard Model observables including potential enhan…
Strange quark as a probe for new physics in the Higgs sector
Alexander Albert, Matthew J. Basso, Samuel K. Bright-Thonney +25
This paper describes a novel algorithm for tagging jets originating from the hadronisation of strange quarks (strange-tagging) with the future International Large Detector (ILD) at…