Variance misspecification in Gaussian mixtures creates a phase diagram: correct specification recovers true means independent of SNR, under-smoothing biases means with SNR^{-1} error in low SNR, and over-smoothing collapses clusters above an SNR-dependent threshold.
A complete data processing workflow for cryo-ET and subtomogram averaging
2 Pith papers cite this work. Polarity classification is still indexing.
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Template matching on pure noise yields asymptotic convergence of maximum-likelihood class means and 3D reconstructions to deterministic noise-dependent transforms of the user templates, producing structure-from-noise artifacts.
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The interplay of signal-to-noise ratio and variance misspecification in Gaussian mixtures
Variance misspecification in Gaussian mixtures creates a phase diagram: correct specification recovers true means independent of SNR, under-smoothing biases means with SNR^{-1} error in low SNR, and over-smoothing collapses clusters above an SNR-dependent threshold.
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Structure from Noise: Confirmation Bias in Particle Picking in Structural Biology
Template matching on pure noise yields asymptotic convergence of maximum-likelihood class means and 3D reconstructions to deterministic noise-dependent transforms of the user templates, producing structure-from-noise artifacts.