12 citations · 21 across the 5 of their papers we have counts for
4 papers · 1 filter
Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Data
Mulugeta Weldezgina Asres, Christian Walter Omlin, The CMS-HCAL Collaboration
Extracting anomaly causality facilitates diagnostics once monitoring systems detect system faults. Identifying anomaly causes in large systems involves investigating a broader set…
Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection
Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang +4
The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation i…
Lightweight Multi-System Multivariate Interconnection and Divergence Discovery
Mulugeta Weldezgina Asres, Christian Walter Omlin, Jay Dittmann +5
Identifying outlier behavior among sensors and subsystems is essential for discovering faults and facilitating diagnostics in large systems. At the same time, exploring large syste…
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…