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The experimental results were better described by a population balance equation using a coalescence kernel that favors growth rate by collision between small and large particles.
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A kernel density estimate using a Gaussian kernel with bandwidth determined by Scott's rule71 was used to estimate the PDFs.
The coordinate-based meta-analysis was performed using a Multilevel Kernel Density Analysis (MKDA 2.
The spot enumeration was done with a kernel density estimation based algorithm [15] using a Gaussian kernel.
Mutual information was computed using a Gaussian Kernel estimate.
Local cell density was estimated with a kernel density estimator using a Gaussian kernel on eight different scales.
Kernels now actually work correctly, but using a non-linear kernel is still very slow.
Multiple kernel learning (MKL) aims at learning a combination of different kernels in order to better match the underlying problem instead of using a single fixed kernel.
Data are resampled using a Gaussian convolution kernel.
Distributions were estimated using a kernel density distribution.
Nonparametric density estimates were generated using a Gaussian smoothing kernel.
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