Results 71 to 80 of about 2,482,864 (253)
Fast Kernel Density Estimation with Density Matrices and Random Fourier Features Software
, 2022 Kernel density estimation (KDE) is one of the most widely used nonparametric density estimation methods. The fact that it is a memory-based method, i.e., it uses the entire training data set for prediction, makes it unsuitable for most current big data ...
Osorio, Juan F. +2 more
core +1 more source
Advanced Functional Materials, EarlyView.This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio +7 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye +8 more
wiley +1 more source
Nonparametric Beta kernel estimator for long memory time series [PDF]
The paper introduces a new nonparametric estimator of the spectral density that is given in smoothing the periodogram by the probability density of Beta random variable (Beta kernel).
VAN BELLEGEM, Sébastien +1 more
core +2 more sources
Image Blind Deblurring Using an Adaptive Patch Prior
Tsinghua Science and Technology, 2019 Image blind deblurring uses an estimated blur kernel to obtain an optimal restored original image with sharp features from a degraded image with blur and noise artifacts.
Yongde Guo, Hongbing Ma
doaj +1 more source
Blind Image Deblurring via Local Maximum Difference Prior
IEEE Access, 2020 Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required.
Jing Liu +4 more
doaj +1 more source
Intracrystalline Void‐Mediated Toughening of Brittle Crystals in Quail Eggshells
Advanced Functional Materials, EarlyView.In quail eggshells, the high density and disordered arrangement of intracrystalline voids inhibit lattice cleavage, suppress long‐range crack propagation, and promote deformation twinning and quasi‐plasticity, serving as an essential toughening motif. We show that these voids remain within a narrow subcritical size range and therefore predominantly do ...
Jingxiao Zhong +16 more
wiley +1 more source
NONPARAMETRIC KERNEL ESTIMATION OF MULTIPLE HEDGE RATIOS [PDF]
It is possible for the traditional hedge ratio estimation to produce erroneous guidance to risk managers because of the restrictive assumptions. This study adopts nonparametric locally polynomial kernel estimation to exclude the assumptions. Results from
Kim, MinKyoung, Leuthold, Raymond M.
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Hemocompatible Glycogen‐Tissue Plasminogen Activator Complexes for Enhanced Blood Clot Dissolution
Advanced Healthcare Materials, EarlyView.Glycogen–heparin‐cRGD nanoparticles enable targeted delivery of tissue plasminogen activator (tPA) to thrombi through activated platelet recognition. The hemocompatible hybrids minimize interactions with blood and immune cells while retaining enzymatic biodegradability.
Nadiia Davydiuk +6 more
wiley +1 more source
sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R [PDF]
The estimation of kernel-smoothed relative risk functions is a useful approach to examining the spatial variation of disease risk. Though there exist several options for performing kernel density estimation in statistical software packages, there have ...
Tilman M. Davies +2 more
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