Introduces tangential Bayes denoiser for Riemannian Gaussian mixtures on manifolds via spectral Laplace-Beltrami approximation, with nearly Bayes risk in low noise and minimax optimality on the circle.
Journal of Applied Statistics , year = 2024, month = feb, volume =
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Negative correlations between biomarkers maximize the combined AUC in multivariate normal models, with the largest gains when markers have equal predictive power, as shown by derivation, simulations, and pancreatic cancer metabolite data.
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Nonparametric Riemannian Empirical Bayes, and Denoising Measurements on Manifolds
Introduces tangential Bayes denoiser for Riemannian Gaussian mixtures on manifolds via spectral Laplace-Beltrami approximation, with nearly Bayes risk in low noise and minimax optimality on the circle.