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University of Cambridge > Talks.cam > Statistics > Identification and Estimation of Graphical Continuous Lyapunov Models
Identification and Estimation of Graphical Continuous Lyapunov ModelsAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Qingyuan Zhao. Note unusual location Graphical continuous Lyapunov models offer a new perspective on modeling causally interpretable dependence structure in multivariate data by treating each independent observation as a one-time cross-sectional snapshot of a temporal process. Specifically, the models consider multivariate Ornstein-Uhlenbeck processes in equilibrium. This leads to Gaussian models in which the covariance matrix is determined by the continuous Lyapunov equation. In this setting, each graphical model assumes a sparse drift matrix with support defined by a directed graph. The talk will discuss the identifiability of such sparse drift matrices and their regularized estimation. This talk is part of the Statistics series. This talk is included in these lists:
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