A functional tensor model with common invariant subspaces and RKHS-based estimation is introduced for dynamic multilayer networks to handle shared structures, temporal smoothness, and layer heterogeneity.
Latent process models for functional network data.arXiv preprint arXiv:2210.07491
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A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation
A functional tensor model with common invariant subspaces and RKHS-based estimation is introduced for dynamic multilayer networks to handle shared structures, temporal smoothness, and layer heterogeneity.