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When Is a Graph a Covariance? Bayesian Residual Propagation under Covariance Uncertainty
Observing a prediction error at one node can help correct predictions elsewhere, but the benefit depends on the residual dependence between nodes. A graph suggests where that dependence might occur, yet does not establish its sign or strength. We develop a Bayesian model of residual covariance to de
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