An interactive visual analytics system integrates two-phase dimensionality reduction, contrastive learning, and multi-resolution dynamic mode decomposition to identify and explain node behavior clusters and anomalies in HPC monitoring data.
Extracting Spatial–Temporal Coherent Patterns in Large-Scale Neural Recordings Using Dynamic Mode Decomposition
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Understanding Large-Scale HPC System Behavior Through Cluster-Based Visual Analytics
An interactive visual analytics system integrates two-phase dimensionality reduction, contrastive learning, and multi-resolution dynamic mode decomposition to identify and explain node behavior clusters and anomalies in HPC monitoring data.