Roddy Taing

On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models

As network data has become ubiquitous in the sciences, there has been growing interest in network models whose structure is driven by latent node-level variables in a (typically low-dimensional) latent geometric space. These "latent positions" are often estimated via embeddings, whereby the nodes of…