Sebastian Moreno Araya

Universidad Adolfo Ibañez

Faculty of Engineering and Science

Building A, Office 212

P. Robles, S. Moreno, and J. Neville *Sampling of Attributed Networks From Hierarchical Generative Models.*

R. Niu, S. Moreno, and J. Neville *Analyzing the Transferability of Collective Inference Models Across Networks.*

S. Moreno, J. Pfeiffer III, J. Neville, and S. Kirshner *A Scalable Method for Exact Sampling from Kronecker Family Models.*

J. Pfeiffer III, S. Moreno, T. La Fond, J. Neville, and B. Gallagher *Attributed Graph Models: Modeling network structure with correlated attributes.*

S. Moreno and J. Neville *Network Hypothesis Testing Using Mixed Kronecker Product Graph Models.*

S. Moreno, S. Kirshner, and J. Neville. *Learning Mixed Kronecker Product Graph Models with Simulated Method of Moments.*

Group probability for Kronecker Models (KPGM and mKPGM) code

mixed Kronecker Product Graph Model code

Network hypothesis testing using mKPGM code

A Scalable Method for Exact Sampling from Kronecker Family Models. In Proceedings of the IEEE International Conference on Data Mining, ICDM 2014.
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Network Hypothesis Testing Using Mixed Kronecker Product Graph Models. In Proceedings of the IEEE International Conference on Data Mining, ICDM 2013.
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Using bayesian network representation for effective sampling from generative network models. Presented at the 5th International Workshop on Statistical Relational AI, 2015.
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Learning Mixed Kronecker Product Graph Models with Simulated Method of Moments. Presented at the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013.
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Block Kronecker Product Graph Model. Presented at 11th Workshop on Mining and Learning with graphs, 2013.
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Statistical Detection of Network-Level Outliers. Presented at NIPS workshop on Scalable Methods for Social Network Analysis, 2012.
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Modeling the variance of Network Populations with Mixed kronecker Product Graph Models. Presented at NIPS workshop on Networks Across Disciplines: Theory and Applications, 2010.
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