Results 1 to 10 of about 1,280,567 (124)
Functional Graphical Models [PDF]
Journal of the American Statistical Association, 2018 Graphical models have attracted increasing attention in recent years, especially in settings involving high-dimensional data. In particular, Gaussian graphical models are used to model the conditional dependence structure among multiple Gaussian random variables.
Qiao, Xinghao +2 more
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Heterogeneous Reciprocal Graphical Models [PDF]
Biometrics, 2017 Summary We develop novel hierarchical reciprocal graphical models to infer gene networks from heterogeneous data. In the case of data that can be naturally divided into known groups, we propose to connect graphs by introducing a hierarchical prior across group-specific graphs, including a correlation on edge strengths across graphs ...
Yang Ni +3 more
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Sum–product graphical models [PDF]
Machine Learning, 2019 This paper introduces a new probabilistic architecture called Sum-Product Graphical Model (SPGM). SPGMs combine traits from Sum-Product Networks (SPNs) and Graphical Models (GMs): Like SPNs, SPGMs always enable tractable inference using a class of models that incorporate context specific independence.
Mattia Desana, Christoph Schnörr
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Transforming Graphical System Models to Graphical Attack Models [PDF]
, 2016 Manually identifying possible attacks on an organisation is a complex undertaking; many different factors must be considered, and the resulting attack scenarios can be complex and hard to maintain as the organisation changes. System models provide a systematic representation of organisations that helps in structuring attack identification and can ...
Ivanova, Marieta Georgieva +3 more
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, 2020 Paired comparison data considered in this paper originate from the comparison of a large number N of individuals in couples. The dataset is a collection of results of contests between two individuals when each of them has faced n opponents, where n is ...
Corff, Sylvain Le +2 more
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Incomplete graphical model inference via latent tree aggregation [PDF]
, 2018 Graphical network inference is used in many fields such as genomics or ecology to infer the conditional independence structure between variables, from measurements of gene expression or species abundances for instance.
Ambroise, Christophe +2 more
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Stratified Graphical Models - Context-Specific Independence in Graphical Models
Bayesian Analysis, 2014 19 pages, 7 png figures. In version two the women and mathematics example is replaced with a parliament election data example.
Nyman, Henrik +3 more
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Interactive analysis of high-dimensional association structures with graphical models [PDF]
, 1998 Graphical chain models are a capable tool for analyzing multivariate data. However, their practical use may still be cumbersome in some respect since fitting the model requires the application of an intensive selection strategy based on the calculation ...
Blauth, Angelika +2 more
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Discussion: Latent variable graphical model selection via convex optimization
, 2012 Discussion of "Latent variable graphical model selection via convex optimization" by Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky [arXiv:1008.1290].Comment: Published in at http://dx.doi.org/10.1214/12-AOS984 the Annals of Statistics ...
Giraud, Christophe, Tsybakov, Alexandre
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, 2016 Structured high-cardinality data arises in many domains, and poses a major challenge for both modeling and inference. Graphical models are a popular approach to modeling structured data but they are unsuitable for high-cardinality variables.
Bui, Hung +5 more
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