Change point detection in temporal graphs
Stage M2 Temporal graphs, which model interactions over time, are essential for analyzing datasets in fields like Industry 4.0 and cybersecurity, but their sparsity and irregularity make change point (CP) detection challenging. Recent research suggests that using time-series and graph dictionaries to transform temporal graphs into new dynamical-structural domains can…
