Results 51 to 60 of about 19,436 (200)

White matter changes and gait decline in cerebral small vessel disease

NeuroImage: Clinical, 2018
The relation between progression of cerebral small vessel disease (SVD) and gait decline is uncertain, and diffusion tensor imaging (DTI) studies on gait decline are lacking.
H.M. van der Holst, A.M. Tuladhar, V. Zerbi, I.W.M. van Uden, K.F. de Laat, E.M.C. van Leijsen, M. Ghafoorian, B. Platel, M.I. Bergkamp, A.G.W. van Norden, D.G. Norris, E.J. van Dijk, A.J. Kiliaan, F.-E. de Leeuw   +13 more
doaj   +1 more source

Color Image Restoration Using Sub-Image Based Low-Rank Tensor Completion

Sensors, 2023
Many restoration methods use the low-rank constraint of high-dimensional image signals to recover corrupted images. These signals are usually represented by tensors, which can maintain their inherent relevance.
Xiaohua Liu, Guijin Tang
doaj   +1 more source

Weighted t-Schatten-p Norm Minimization for Real Color Image Denoising

IEEE Access, 2020
In this paper, to fully exploit the spatial and spectral correlation information, we present a new real color image denoising scheme using tensor Schatten-p norm (t-Schatten-p norm) minimization based on t-SVD to recover the underlying low-rank tensor ...
Min Liu, Xinggan Zhang, Lan Tang
doaj   +1 more source

Hyper-Laplacian Regularized Multi-View Subspace Clustering With a New Weighted Tensor Nuclear Norm

IEEE Access, 2021
In this paper, we present a hyper-Laplacian regularized method WHLR-MSC with a new weighted tensor nuclear norm for multi-view subspace clustering. Specifically, we firstly stack the subspace representation matrices of the different views into a tensor ...
Qingjiang Xiao, Shiqiang Du, Jinmei Song, Yao Yu, Yixuan Huang   +4 more
doaj   +1 more source

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

Advanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio, Tommaso Gili, Andrea Gabrielli, Maurizio Mattia   +3 more
wiley   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Structural network efficiency predicts cognitive decline in cerebral small vessel disease

NeuroImage: Clinical, 2020
Cerebral small vessel disease (SVD) is a common disease in older adults and a major contributor to vascular cognitive impairment and dementia. White matter network damage is a potentially important mechanism by which SVD causes cognitive impairment ...
Esther M. Boot, Esther MC van Leijsen, Mayra I. Bergkamp, Roy P.C. Kessels, David G. Norris, Frank-Erik de Leeuw, Anil M. Tuladhar   +6 more
doaj   +1 more source

A Tensor SVD-based Classification Algorithm Applied to fMRI Data

SIAM Undergraduate Research Online, 2022
To analyze the abundance of multidimensional data, tensor-based frameworks have been developed. Traditionally, the matrix singular value decomposition (SVD) is used to extract the most dominant features from a matrix containing the vectorized data. While the SVD is highly useful for data that can be appropriately represented as a matrix, this step of ...
Keegan, Katherine, Vishwanath, Tanvi, Xu, Yihua   +2 more
openaire   +2 more sources

Quenching the Hubbard Model: Comparison of Nonequilibrium Green's Function Methods

Contributions to Plasma Physics, EarlyView.
ABSTRACT We benchmark nonequilibrium Green's function (NEGF) approaches for interaction quenches in the half‐filled Fermi–Hubbard model in one and two dimensions. We compare fully self‐consistent two‐time Kadanoff–Baym equations (KBE), the generalized Kadanoff–Baym ansatz (GKBA), and the recently developed NEGF‐based quantum fluctuations approach (NEGF‐
Jan‐Philip Joost, Christopher Makait, Alexander Osterkorn, Erik Schroedter   +3 more
wiley   +1 more source

Tensor and Matrix Inversions with Applications [PDF]

, 2011
Higher order tensor inversion is possible for even order. We have shown that a tensor group endowed with the Einstein (contracted) product is isomorphic to the general linear group of degree $n$.
Brazell, Michael, Li, Na, Navasca, Carmeliza, Tamon, Christino   +3 more
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