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Tensor Computation for Data Analysis

Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss;

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Tensors for Data Processing

Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor;

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Tensor Networks for Dimensionality Reduction and Large-scale Optimization

and valuable for the multidisciplinary machine learning and data analytic communities to review tensor decompositions and tensor networks as;

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Computation of Nonlinear Structures

differential geometry, mesh generation, tensor analysis with particular elaboration on rotation tensor, finite element methodology and numerical;

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Matrix and Tensor Decompositions in Signal Processing

very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the;

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The Visualization of Second-Order Tensor Fields

of visualization techniques for second-order tensor fields. Tensor fields are multivariate; they can embed as much information as n squared scalar fields;

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Application of Omics, AI and Blockchain in Bioinformatics Research

of the diseases.A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics;

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Tensor Numerical Methods in Quantum Chemistry

tensor decomposition originating from chemometrics made a revolution in numerical analysis, relying on rigorous results from approximation;

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Theory and Computation of Complex Tensors and its Applications

authors design the neural network model for the computation of the rank-one approximation of real tensors, a normalization algorithm to convert;

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Theory and Computation of Complex Tensors and its Applications

authors design the neural network model for the computation of the rank-one approximation of real tensors, a normalization algorithm to convert;

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New Developments in the Visualization and Processing of Tensor Fields

analysis and visualization of tensor fields, which offer a concise model for numerous physical phenomena. Despite their utility, there remains a;

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New Developments in the Visualization and Processing of Tensor Fields

analysis and visualization of tensor fields, which offer a concise model for numerous physical phenomena. Despite their utility, there remains a;

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Tensor Analysis

Tensor calculus is a prerequisite for many tasks in physics and engineering. This book introduces the symbolic and the index notation side;

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Thermofluid Dynamics of Turbulent Flows

tensor notation, which is the most appropriate to deal with intrinsically tensor quantities such as stresses and strain rates, and for those who;

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Thermofluid Dynamics of Turbulent Flows

tensor notation, which is the most appropriate to deal with intrinsically tensor quantities such as stresses and strain rates, and for those who;

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Neural Data Science

MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the;

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Vector and Tensor Analysis

can well be recommended." NatureHere is a clear introduction to classic vector and tensor analysis for students of engineering and;

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Evolutionary Computation Machine Learning and Data Mining in Bioinformatics

This book constitutes the refereed proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining;

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Non-Negative Matrix And Tensor Factorizations

their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their;

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Tensor Algebra and Tensor Analysis for Engineers

This is the fifth and revised edition of a well-received textbook that aims at bridging the gap between the engineering course of tensor;

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Tensor Categories

Is there a vector space whose dimension is the golden ratio? Of course not-the golden ratio is not an integer! But this can happen for;

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Topological Data Analysis for Scientific Visualization

methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with;

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Topological Data Analysis for Scientific Visualization

methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with;

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Elasticity with Mathematica

is introduced for elastostatic and spectral analysis problems. Containing more than 60 exercises and solutions in the form of Mathematica notebooks that;

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Elasticity With Mathematica

is introduced for elastostatic and spectral analysis problems. Containing more than 60 exercises and solutions in the form of Mathematica notebooks that;

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Tensor analysis with Applications

The principal aim of tensor analysis is to investigate the relations which remain valid when we change from one coordinate system to;

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Visualization of Fields and Applications in Engineering

of Fields and Applications in Engineering presents the basic techniques for tensor field visualization and mapping of engineering data. Focusing on;

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