A Mutually Exciting Latent Space Hawkes Process Model for Continuous-time NetworksDownload PDF

Published: 20 May 2022, Last Modified: 05 May 2023UAI 2022 PosterReaders: Everyone
Keywords: dynamic network model, latent space model, temporal point process, multivariate Hawkes process, relational events
TL;DR: We propose a mutually exciting latent space Hawkes model, a novel generative model for such continuous-time networks of relational events using a latent space representation for nodes.
Abstract: Networks and temporal point processes serve as fundamental building blocks for modeling complex dynamic relational data in various domains. We propose the latent space Hawkes (LSH) model, a novel generative model for continuous-time networks of relational events, using a latent space representation for nodes. We model relational events between nodes using mutually exciting Hawkes processes with baseline intensities dependent upon the distances between the nodes in the latent space and sender and receiver specific effects. We demonstrate that our proposed LSH model can replicate many features observed in real temporal networks including reciprocity and transitivity, while also achieving superior prediction accuracy and providing more interpretable fits than existing models.
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