Sampling and inference for beta neutral-to-the-left models of sparse networks

Sampling and inference for beta neutral-to-the-left models of sparse networks

Empirical evidence suggests that heavy-tailed degree distributions occurring in many real networks are well-approximated by power laws with exponents η that may take values either less than and greater than two. Models based on various forms of exchangeability are able to capture power laws with η &...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy:	Bloem-Reddy, B, Foster, A, Mathieu, E, Teh, Y
Format:	Conference item
Wydane:	AUAI Press 2018

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