A Bayesian CP tensor factorization model with Poisson rate for occurrence and conditional Gamma for magnitude, with slice-specific dispersion, applied to 60 million international trade flows to recover multiway dependencies.
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Hub importance scores persist more strongly between functionally similar layers than dissimilar ones in multilayer networks, as evidenced by 31 pre-registered experiments across eight fields.
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Bayesian Poisson-Randomized Gamma Tensor Factorization with Application to International Trade Flows
A Bayesian CP tensor factorization model with Poisson rate for occurrence and conditional Gamma for magnitude, with slice-specific dispersion, applied to 60 million international trade flows to recover multiway dependencies.
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Evidence for a Functional Proximity Law in Multilayer Networks
Hub importance scores persist more strongly between functionally similar layers than dissimilar ones in multilayer networks, as evidenced by 31 pre-registered experiments across eight fields.