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Upper-bound on the Fisher-Rao Distancedistance between Multivariatemultivariate Gaussian measures by the KL-divergence

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Upper-bound on the Fisher-Rao Distance between Multivariate Gaussian measures by the KL-divergence

Let $\mu$ and $\nu$ be two multivariate Gaussian measures on $\mathbb{R}^d$ with non-singular covariance matrices. Can the Fisher-Rao distance $d(\mu,\nu)$ computed on the information manifold of non-generated $d$-dimensional Gaussian measures with Fisher-Rao metric, be bounded by the (symmetrized) KL divergence/relative-entropy between $\mu$ and $\nu$?