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The aim of the bootstrapping technique [6] is to estimate the sampling distribution of an estimator by sampling with replacement from a given sample. It is a ...
In this work, we examine bootstrap techniques for classifying the projection data. When these techniques are applied to variance estimation, the projection ...
In this work, we examine bootstrap techniques for classifying the projection data. When these techniques are applied to variance estimation, the projection ...
This work examines bootstrap techniques for classifying the projection data in single-particle reconstruction methods and explains the rationale of these ...
In single-particle reconstruction methods [1], projections of macromolecules at randomly unknown orientations are collected by an electron microscope.
In single-particle reconstruction methods, projections of macromolecules at random orientations are collected. Often, several classes of conformations or ...
CLASSIFICATION BY BOOTSTRAPPING IN SINGLE PARTICLE METHODS. In single-particle reconstruction methods, projections of macromolecules at random orientations ...
The term "bootstrap model" is used for a class of theories that use ... Bootstrapping here refers to 'pulling oneself up by one's bootstraps,' as particles ...
Missing: Classification single
Variational bootstrap provides a way to obtain samples from the posterior distribution over model parameters, where each sample is the solution of a task where ...
The bootstrapping approach is performed by randomly selecting particle images or class ... One classification approach is via the covariance matrix, which ...