Results 271 to 280 of about 1,245,381 (307)

Abnormal alterations in structure-function coupling at the modular level in patients with postherpetic neuralgia. [PDF]

Sci Rep
Li Z, Jiang J, Jiang X, Xie Y, Lu J, Gu L, Hong S.   +6 more
europepmc   +1 more source

Prioritizing drug targets by perturbing biological network response functions. [PDF]

PLoS Comput Biol
Perrone MC, Lerner MG, Dunworth M, Ewald AJ, Bader JS.   +4 more
europepmc   +1 more source

An Improved Vital Signal Extraction Method Based on Laser Doppler Effect. [PDF]

Sensors (Basel)
Li Y, Zhang H, Zhang B, Qi Y, Chen S.
europepmc   +1 more source

Relative strength variability measures for brain structural connectomes and their relationship with cognitive functioning

Yeung HW, Buchanan CR, Moodie J, Deary IJ, Tucker-Drob EM, Bastin ME, Whalley HC, Smith KM, Cox SR.   +8 more
europepmc   +1 more source

Direct Decomposition Theory of Torsion-Free Abelian Groups of Finite Rank: Graph Method [PDF]

Lobachevskii Journal of Mathematics, 2018
Graphical direct decomposition theory of block-rigid almost completely decomposable groups with cyclic regulator quotient is substantiated and effectively applied to construction of a group with predicted set of its direct decompositions up to near isomorphism.
E. A. Blagoveshchenskaya, Danielle Kunetz   +1 more
semanticscholar   +3 more sources

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Hyperspectral Image Denoising Using Adaptive Weight Graph Total Variation Regularization and Low-Rank Matrix Recovery

IEEE Geoscience and Remote Sensing Letters, 2022
Hyperspectral image (HSI) is often corrupted by various kinds of noises. This letter proposes an innovative HSI denoising approach by leveraging the graph signal processing (GSP) theory and the low-rank (LR) matrix recovery model. With GSP, the piecewise
Wanyuan Cai, Junzheng Jiang, S. Ouyang
semanticscholar   +1 more source

Hyperspectral Image Destriping and Denoising Using Stripe and Spectral Low-Rank Matrix Recovery and Graph Laplacian Regularization

Chinese Control and Decision Conference, 2022
Hyperspectral images are often degraded by various types of noise. It is important to choose appropriate image priors for the underdetermined imaging denoising problems.
Xin Chen, Fang Yang
semanticscholar   +1 more source

Graph-Theory-Based Molecular Fragmentation for Efficient and Accurate Potential Surface Calculations in Multiple Dimensions.

Journal of Chemical Theory and Computation, 2021
We present a multitopology molecular fragmentation approach, based on graph theory, to calculate multidimensional potential energy surfaces in agreement with post-Hartree-Fock levels of theory but at the density functional theory cost.
Anup Kumar, Nicole DeGregorio, S. Iyengar   +2 more
semanticscholar   +1 more source

On the Asymptotic Nonnegative Rank of Matrices and its Applications in Information Theory

International Symposium on Information Theory, 2023
In this paper, we study the asymptotic nonnegative rank of matrices, which characterizes the asymptotic growth of the nonnegative rank of fixed nonnegative matrices under the Kronecker product.
Yeow Meng Chee, Quoc-Tung Le, Hoang Ta
semanticscholar   +1 more source

A directed link prediction method using graph convolutional network based on social ranking theory

Intelligent Data Analysis, 2021
Graph convolutional networks (GCN) have recently emerged as powerful node embedding methods in network analysis tasks. Particularly, GCNs have been successfully leveraged to tackle the challenging link prediction problem, aiming at predicting missing links that exist yet were not found.
Shuxin Liu, Hongchang Chen, Yulong Pei, Zheng Wu, Jianpeng Zhang, Ruiyang Huang   +5 more
openaire   +2 more sources