Results 61 to 70 of about 115,711 (260)
Ядерна фізика та енергетика, 2019 Within the framework of the problem of spectrum deconvolution, variant of the choice of the regularization parameter by criterion of the L-curve, based on the displacement along the points of the L-curve graph, is proposed. An analysis of dependencies on
A. M. Sokolov
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Optimal regular graph designs [PDF]
Statistics and Computing, 2017 A typical problem in optimal design theory is finding an experimental design that is optimal with respect to some criteria in a class of designs. The most popular criteria include the A- and D-criteria. Regular graph designs occur in many optimality results and, if the number of blocks is large enough, they are A- and D-optimal.
openaire +3 more sources
Advanced Science, EarlyView.The prevailing neglect of cellular hierarchies in current spatial transcriptomics deconvolution often obscures cellular heterogeneity and impedes the identification of fine‐grained subtypes. To address this issue, HIDF employs a cluster‐tree and dual regularization to systematically model cellular hierarchical structures.
Zhiyi Zou +5 more
wiley +1 more source
Semantic Consistency Cross-Modal Retrieval With Semi-Supervised Graph Regularization
IEEE Access, 2020 Most of the existing cross-modal retrieval methods make use of labeled data to learn projection matrices for different modal data. These methods usually learn the original semantic space to bridge the heterogeneous gap, ignoring the rich semantic ...
Gongwen Xu, Xiaomei Li, Zhijun Zhang
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Motivic renormalization and singularities [PDF]
, 2009 We consider parametric Feynman integrals and their dimensional regularization from the point of view of differential forms on hypersurface complements and the approach to mixed Hodge structures via oscillatory integrals.
Marcolli, Matilde
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Deep Graph Laplacian Regularization for Robust Denoising of Real Images
, 2019 Recent developments in deep learning have revolutionized the paradigm of image restoration. However, its applications on real image denoising are still limited, due to its sensitivity to training data and the complex nature of real image noise.
Cheung, Gene +3 more
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Advanced Science, EarlyView.HiST, a multiscale deep learning framework, reconstructs spatially resolved gene expression profiles directly from histological images. It accurately identifies tumor regions, captures intratumoral heterogeneity, and predicts patient prognosis and immunotherapy response.
Wei Li +8 more
wiley +1 more source
Cross-media retrieval method fusing with coupled dictionary learning and image regularization [PDF]
Jisuanji gongcheng, 2019 The method of cross-media retrieval mostly maps the original features of two modalities to the common subspace,and performs cross-media retrieval in the subspace,ignoring the selection of discriminant features and the relationship between modalities ...
LIU Yun,YU Zhilou,FU Qiang
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Vacuum Polarization and Chiral Lattice Fermions
, 1995 The vacuum polarization due to chiral fermions on a 4--dimensional Euclidean lattice is calculated according to the overlap prescription. The fermions are coupled to weak and slowly varying background gauge and Higgs fields, and the polarization tensor ...
't Hooft +52 more
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Advanced Science, EarlyView.IGF‐1 deficiency underlies poor ovarian response (POR), as reduced levels in follicular fluid and granulosa cells impair antral follicle formation and compromise reproductive outcomes. Including IGF‐1 as a biomarker significantly enhances the accuracy of models predicting both PORrisk and pregnancy success.
Zhu Hu +9 more
wiley +1 more source