Relation between graph Laplacians and covariance matrices

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In the "Future challenges" section of the article Dittrich, Thomas, and Gerald Matz. "Signal processing on signed graphs: Fundamentals and potentials." IEEE Signal Processing Magazine 37.6 (2020): 86-98, there is the following claim: "It is folklore knowledge that graph Laplacians can be related to inverse covariance matrices". I cannot see this connection, and the article does not include any reference to support this claim. Any help regarding the connection between graph Laplacians and covariance matrices would be inmensely helpful.