Persistent homology on thresholded dynamic graphs from DBNs yields stable barcodes that summarize the temporal evolution of strongly dependent variable clusters.
Adaptive Computation and Machine Learning
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A Stable Distance Persistence Homology for Dynamic Bayesian Network Clustering
Persistent homology on thresholded dynamic graphs from DBNs yields stable barcodes that summarize the temporal evolution of strongly dependent variable clusters.