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Kernel Estimation in High-Energy Physics

4 Pith papers cite this work. Polarity classification is still indexing.

4 Pith papers citing it
abstract

Kernel Estimation provides an unbinned and non-parametric estimate of the probability density function from which a set of data is drawn. In the first section, after a brief discussion on parametric and non-parametric methods, the theory of Kernel Estimation is developed for univariate and multivariate settings. The second section discusses some of the applications of Kernel Estimation to high-energy physics. The third section provides an overview of the available univariate and multivariate packages. This paper concludes with a discussion of the inherent advantages of kernel estimation techniques and systematic errors associated with the estimation of parent distributions.

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2026 3 2025 1

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representative citing papers

Charged-lepton identification at Belle~II

hep-ex · 2026-06-24 · unverdicted · novelty 3.0

Belle II describes its charged-lepton identification algorithms and reports performance on 428 fb^{-1} of Run 1 data from SuperKEKB.

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Showing 4 of 4 citing papers.