Performances estimation for tensor CP decomposition with structured factors [PDF]
, 2015 International audienceThe Canonical Polyadic tensor decomposition (CPD), also known as Candecomp/Parafac, is very useful in numerous scientific disciplines. Structured CPDs, i.e.
Cohen, Jérémy, +12 more
core +1 more source
Knowledge Graph Reasoning Based on Tensor Decomposition and MHRP-Learning
Advances in Multimedia, 2021 In the process of learning and reasoning knowledge graph, the existing tensor decomposition technology only considers the direct relationship between entities in knowledge graph. However, it ignores the characteristics of the graph structure of knowledge
Tangsen Huang +3 more
doaj +1 more source
Ideal minimal residual-based proper generalized decomposition for non-symmetric multi-field models – Application to transient elastodynamics in space-time domain [PDF]
, 2014 It is now well established that separated representations built with the help of proper generalized decomposition (PGD) can drastically reduce computational costs associated with solution of a wide variety of problems.
BOUCINHA, Lucas +3 more
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Decomposition of Elasticity Tensor on Material Constants and Mesostructures of Metal Plates
CrystalsMost metal plates are orthorhombic aggregates of cubic crystallites. First, we discuss the representations of the stress tensor, the strain tensor, the elasticity tensor, and the rotation tensor under the Kelvin notation.
Genbao Liu +5 more
doaj +1 more source
A Color Image Watermarking Based on Tensor Analysis
IEEE Access, 2018 Since most of the color image watermarking methods embed the watermark information in each channel or one channel of a color image, the redundant information of the color image cannot be sufficiently utilized, resulting in the poor ability to resist ...
Haiyong Xu +3 more
doaj +1 more source
A tensor compression algorithm using Tucker decomposition and dictionary dimensionality reduction
International Journal of Distributed Sensor Networks, 2020 Tensor compression algorithms play an important role in the processing of multidimensional signals. In previous work, tensor data structures are usually destroyed by vectorization operations, resulting in information loss and new noise. To this end, this
Chenquan Gan +3 more
doaj +1 more source
Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Conventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively.
Apisit Kaewsanit +10 more
wiley +1 more source
Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs [PDF]
, 2012 We describe an approach to speed-up inference with latent-variable PCFGs, whichhave been shown to be highly effective for natural language parsing. Our approachis based on a tensor formulation recently introduced for spectral estimation oflatent-variable
Collins, Michael, Cohen, Shay
core
Nonnegative tensor CP decomposition of hyperspectral data
, 2016 International audienceNew hyperspectral missions will collect huge amounts of hyperspectral data. Besides, it is possible now to acquire time series and multiangular hyperspectral images.
Cohen, Jérémy, +5 more
core +1 more source
Advanced Engineering Materials, EarlyView.The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ +19 more
wiley +1 more source