# Tensor decomposition and applications

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/tensor-decomposition-and-applications/

## Facts

| Field | Value |
| --- | --- |
| Citations | 287,740 |
| Description | This cluster of papers focuses on the theory and applications of tensor decompositions, particularly in the context of multilinear algebra. It covers various decomposition methods such as Singular Value Decomposition, Parallel Factor Analysis, Canonical Polyadic Decomposition, and Tucker Decomposition, along with their applications in signal processing and machine learning. |
| Domain | Physical Sciences |
| Field | Mathematics |
| OpenAlex ID | https://openalex.org/T12303 |
| Works | 24,204 |

## Topic papers all

- [On Unifying Multi-view Self-Representations for Clustering by Tensor Multi-rank Minimization](https://scholariq.org/papers/on-unifying-multi-view-self-representations-for-clustering-by-tensor-multi-rank/)
- [Cognitive functions correlate with white matter architecture in a normal pediatric population: A diffusion tensor MRI study](https://scholariq.org/papers/cognitive-functions-correlate-with-white-matter-architecture-in-a-normal/)
- [Simultaneous Tensor Decomposition and Completion Using Factor Priors](https://scholariq.org/papers/simultaneous-tensor-decomposition-and-completion-using-factor-priors/)
- [Low rank tensor completion for multiway visual data](https://scholariq.org/papers/low-rank-tensor-completion-for-multiway-visual-data/)
- [Improved Robust Tensor Principal Component Analysis via Low-Rank Core Matrix](https://scholariq.org/papers/improved-robust-tensor-principal-component-analysis-via-low-rank-core-matrix/)
- [Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion](https://scholariq.org/papers/maximum-likelihood-estimation-for-the-tensor-normal-distribution-algorithm/)
- [Application of deep canonically correlated sparse autoencoder for the classification of schizophrenia](https://scholariq.org/papers/application-of-deep-canonically-correlated-sparse-autoencoder-for-the/)
- [Advanced Insights into Functional Brain Connectivity by Combining Tensor Decomposition and Partial Directed Coherence](https://scholariq.org/papers/advanced-insights-into-functional-brain-connectivity-by-combining-tensor/)
- [Widespread white matter connectivity abnormalities in narcolepsy type 1: A diffusion tensor imaging study](https://scholariq.org/papers/widespread-white-matter-connectivity-abnormalities-in-narcolepsy-type-1-a/)

## Topic researchers

Showing 12 of 20.

- [Xiaogang Wang](https://scholariq.org/researchers/xiaogang-wang/)
- [Clifford R. Jack](https://scholariq.org/researchers/clifford-r-jack/)
- [Paul M. Thompson](https://scholariq.org/researchers/paul-m-thompson/)
- [Demis Hassabis](https://scholariq.org/researchers/demis-hassabis/)
- [Anders M. Dale](https://scholariq.org/researchers/anders-m-dale/)
- [Michael I. Jordan](https://scholariq.org/researchers/michael-i-jordan/)
- [Nick C. Fox](https://scholariq.org/researchers/nick-c-fox/)
- [David Silver](https://scholariq.org/researchers/david-silver/)
- [Philip S. Yu](https://scholariq.org/researchers/philip-s-yu/)
- [Arthur W. Toga](https://scholariq.org/researchers/arthur-w-toga/)
- [Michael W. Weiner](https://scholariq.org/researchers/michael-w-weiner/)
- [Pushmeet Kohli](https://scholariq.org/researchers/pushmeet-kohli/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.