An intrinsic effective sample size for manifold MCMC is defined via kernel discrepancy as the number of independent draws yielding equivalent expected squared discrepancy to the target.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.
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A Machine Learning Approach to Meteor Classification
Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.