Rm-NML is introduced as a geometrically invariant extension of NML to Riemannian manifolds, with explicit computation shown for normal distributions on hyperbolic spaces.
Gaussian distributions on riemannian symmetric spaces: statistical learning with structured covariance matrices
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Normalized Maximum Likelihood Code-Length on Riemannian Data Spaces
Rm-NML is introduced as a geometrically invariant extension of NML to Riemannian manifolds, with explicit computation shown for normal distributions on hyperbolic spaces.