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Published in 2021 at "Nuclear Physics B"
DOI: 10.1016/j.nuclphysb.2021.115582
Abstract: We show that the Riemannian Gaussian distributions on symmetric spaces, introduced in recent years, are of standard random matrix type. We exploit this to compute analytically marginals of the probability density functions. This can be…
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Keywords:
riemannian gaussian;
diffusion;
random matrix;
case ... See more keywords
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Published in 2022 at "IEEE Transactions on Information Theory"
DOI: 10.1109/tit.2022.3199479
Abstract: Riemannian Gaussian distributions were initially introduced as basic building blocks for learning models which aim to capture the intrinsic structure of statistical populations of positive-definite matrices (here called covariance matrices). While the potential applications of…
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Keywords:
covariance matrices;
dimensional covariance;
random matrix;
covariance ... See more keywords