Results 81 to 90 of about 120,823 (294)
Fourier–Bessel heat kernel estimates
Journal of Mathematical Analysis and Applications, 2016 11 ...
Małecki, Jacek +2 more
openaire +2 more sources
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Estimation of Star-Shaped Distributions
Risks, 2016 Scatter plots of multivariate data sets motivate modeling of star-shaped distributions beyond elliptically contoured ones. We study properties of estimators for the density generator function, the star-generalized radius distribution and the density in a
Eckhard Liebscher, Wolf-Dieter Richter
doaj +1 more source
On the nonparametric estimation of the functional expectile regression
Comptes Rendus. Mathématique, 2020 In this note, we investigate the kernel-type estimator of the nonparametric expectile regression model for functional data. More precisely, we establish the almost complete convergence rate of this estimator under some mild conditions.
Mohammedi, Mustapha +2 more
doaj +1 more source
Estimation of the Error Density in a Semiparametric Transformation Model
, 2011 Consider the semiparametric transformation model $\Lambda_{\theta_o}(Y)=m(X)+\epsilon$, where $\theta_o$ is an unknown finite dimensional parameter, the functions $\Lambda_{\theta_o}$ and $m$ are smooth, $\epsilon$ is independent of $X$, and $\esp ...
Heuchenne, Cédric +2 more
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Variational Dirichlet Blur Kernel Estimation
IEEE Transactions on Image Processing, 2015 Blind image deconvolution involves two key objectives: 1) latent image and 2) blur estimation. For latent image estimation, we propose a fast deconvolution algorithm, which uses an image prior of nondimensional Gaussianity measure to enforce sparsity and an undetermined boundary condition methodology to reduce boundary artifacts. For blur estimation, a
Xu, Zhou +4 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley +1 more source
Ensemble Estimation of Information Divergence †
Entropy, 2018 Recent work has focused on the problem of nonparametric estimation of information divergence functionals between two continuous random variables. Many existing approaches require either restrictive assumptions about the density support set or difficult ...
Kevin R. Moon +3 more
doaj +1 more source
Bayesian selector of adaptive bandwidth for multivariate gamma kernel estimator on [0,∞ ) d. [PDF]
J Appl Stat, 2022 Somé SM, Kokonendji CC.
europepmc +1 more source
Kernel Methods for Small Sample and Asymptotic Tail Inference for Dependent, Heterogeneous Data [PDF]
This paper considers tail shape inference techniques robust to substantial degrees of serial dependence and heterogeneity. We detail a new kernel estimator of the asymptotic variance and the exact small sample mean-squared-error, and a simple ...
Jonathan Hill
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