Semiparametric Differential Graph Models

Pan Xu, Quanquan Gu

Neural Information Processing Systems 

In many cases of network analysis, it is more attractive to study how a network varies under different conditions than an individual static network. We propose a novel graphical model, namely Latent Differential Graph Model, where the networks under two different conditions are represented by two semiparametric elliptical distributions respectively, and the variation of these two networks ( i.e.,

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