Scalable and exact sampling method for probabilistic generative graph models
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Publication:2287714
DOI10.1007/s10618-018-0566-xzbMath1428.62061OpenAlexW2802870214WikidataQ114827248 ScholiaQ114827248MaRDI QIDQ2287714
Joseph J. III Pfeiffer, Jennifer Neville, Sebastián Moreno
Publication date: 21 January 2020
Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10618-018-0566-x
Social networks; opinion dynamics (91D30) Small world graphs, complex networks (graph-theoretic aspects) (05C82) Statistical sampling theory and related topics (62D99)
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- Logit models and logistic regressions for social networks. I: An introduction to Markov graphs and \(p^*\)
- A preferential attachment model with random initial degrees
- Generating the maximum of independent identically distributed random variables
- A Scalable Generative Graph Model with Community Structure
- Emergence of Scaling in Random Networks
- ON A CLASS OF SKEW DISTRIBUTION FUNCTIONS
- Markov Graphs
- An Exponential Family of Probability Distributions for Directed Graphs
- Learning latent block structure in weighted networks
- Moment-Based Estimation of Stochastic Kronecker Graph Parameters
- Algorithms and Models for the Web-Graph
- Collective dynamics of ‘small-world’ networks
- The average distances in random graphs with given expected degrees
- The Kolmogorov-Smirnov Test for Goodness of Fit
- Multiplicative Attribute Graph Model of Real-World Networks
- Dynamics of directed graphs: The world-wide Web
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