Results 81 to 90 of about 415,263 (295)
On almost sure convergence rates for the kernel estimator of a covariance operator under negative association [PDF]
It is suppose that $\{X_n,~n\geq 1\}$ is a strictly stationary sequence of negatively associated random variables with continuous distribution function F.
Hadi Jabbari
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AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source
Blind Image Deblurring via Local Maximum Difference Prior
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
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Fourier–Bessel heat kernel estimates
11 ...
Małecki, Jacek +2 more
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Flexoelectrically Induced Polar Topology in Twisted SrTiO3 Membranes
Twisted SrTiO3 bilayers host polar vortices of flexoelectric origin, revealed through combined experiment and theory. By reconstructing polarization from the toroidal moment of strain gradients, the work establishes a 3D chiral state with broken inversion and mirror symmetries.
Isabel Tenreiro +13 more
wiley +1 more source
This paper investigates the asymptotic behavior of kernel-based estimators for the error distribution in a first-order autoregressive model with dependent errors. The model assumes that the error terms form an α-mixing sequence with an unknown cumulative
Bing Wang +4 more
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Kernel Exponential Family Estimation via Doubly Dual Embedding [PDF]
We investigate penalized maximum log-likelihood estimation for exponential family distributions whose natural parameter resides in a reproducing kernel Hilbert space.
Dai, Bo +5 more
core +1 more source
Variational Dirichlet Blur Kernel Estimation
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
Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur +7 more
wiley +1 more source
Pseudo likelihood and dimension reduction for data with nonignorable nonresponse
Tang et al. (2003. Analysis of multivariate missing data with nonignorable nonresponse. Biometrika, 90(4), 747–764) and Zhao & Shao (2015. Semiparametric pseudo-likelihoods in generalized linear models with nonignorable missing data.
Ji Chen, Bingying Xie, Jun Shao
doaj +1 more source

