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Information Geometry for the Working Information Theorist
Information geometry is a study of statistical manifolds, that is, spaces of probability distributions from a geometric perspective.
Information Geometry and Classical Cramér-Rao Type Inequalities
We examine the role of information geometry in the context of classical Cram\'er-Rao (CR) type inequalities.
Generalized Bayesian Cramér-Rao Inequality via Information Geometry of Relative $α$-Entropy
The relative $\alpha$-entropy is the R\'enyi analog of relative entropy and arises prominently in information-theoretic problems.
Cramér-Rao Lower Bounds Arising from Generalized Csiszár Divergences
We study the geometry of probability distributions with respect to a generalized family of Csisz\'ar $f$-divergences.
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