A multi-stage smoothing estimator is developed to estimate time-varying network edge probabilities under Hölder smoothness and piecewise Lipschitz conditions.
Change-point detection in dynamic networks via graphon estimation
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MENT imposes isotropic normalization on anchor latent positions in unfolded spectral embeddings to preserve second-moment geometry under orthogonal transformations, yielding consistent multiscale trajectories for dynamic network interpretation and inference.
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Nonparametric estimation of time-varying network connections by multi-stage smoothing
A multi-stage smoothing estimator is developed to estimate time-varying network edge probabilities under Hölder smoothness and piecewise Lipschitz conditions.
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Multiscale Euclidean Network Trajectories: Second-Moment Geometry, Attribution, and Change Points
MENT imposes isotropic normalization on anchor latent positions in unfolded spectral embeddings to preserve second-moment geometry under orthogonal transformations, yielding consistent multiscale trajectories for dynamic network interpretation and inference.