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Tensors in statistics
This article provides an overview of tensors, their properties, and their applications in
statistics. Tensors, also known as multidimensional arrays, are generalizations of matrices to …
statistics. Tensors, also known as multidimensional arrays, are generalizations of matrices to …
A contemporary and comprehensive survey on streaming tensor decomposition
Tensor decomposition has been demonstrated to be successful in a wide range of
applications, from neuroscience and wireless communications to social networks. In an …
applications, from neuroscience and wireless communications to social networks. In an …
Tensor based temporal and multilayer community detection for studying brain dynamics during resting state fMRI
Objective: In recent years, resting state fMRI has been widely utilized to understand the
functional organization of the brain for healthy and disease populations. Recent studies …
functional organization of the brain for healthy and disease populations. Recent studies …
Learning to summarize Chinese radiology findings with a pre-trained encoder
Automatic radiology report summarization has been an attractive research problem towards
computer-aided diagnosis to alleviate physicians' workload in recent years. However …
computer-aided diagnosis to alleviate physicians' workload in recent years. However …
Data-driven retrieval of population-level EEG features and their role in neurodegenerative diseases
W Li, Y Varatharajah, E Dicks, L Barnard… - Brain …, 2024 - academic.oup.com
Electrophysiologic disturbances due to neurodegenerative disorders such as Alzheimer's
disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional …
disease and Lewy Body disease are detectable by scalp EEG and can serve as a functional …
Temporal segmentation of EEG based on functional connectivity network structure
Z Xu, S Tang, C Liu, Q Zhang, H Gu, X Li, Z Di, Z Li - Scientific Reports, 2023 - nature.com
In the study of brain functional connectivity networks, it is assumed that a network is built
from a data window in which activity is stationary. However, brain activity is non-stationary …
from a data window in which activity is stationary. However, brain activity is non-stationary …
Neighbor graph based tensor recovery for accurate internet anomaly detection
Detecting anomalous traffic is a crucial task for network management. Although many
anomaly detection algorithms have been proposed recently, constrained by their matrix …
anomaly detection algorithms have been proposed recently, constrained by their matrix …
Measuring multivariate phase synchronization with symbolization and permutation
Z Li, X Wang, Y **ng, X Zhang, T Yu, X Li - Neural Networks, 2023 - Elsevier
Phase synchronization is an important mechanism for the information processing of neurons
in the brain. Most of the current phase synchronization measures are bivariate and focus on …
in the brain. Most of the current phase synchronization measures are bivariate and focus on …
Enhanced network traffic anomaly detection: Integration of tensor eigenvector centrality with low-rank recovery models
In service computing, network traffic anomaly detection is pivotal for monitoring and
identifying irregularities in network traffic to uphold the security, reliability, and stability of …
identifying irregularities in network traffic to uphold the security, reliability, and stability of …
Deriving electrophysiological brain network connectivity via tensor component analysis during freely listening to music
Recent studies show that the dynamics of electrophysiological functional connectivity is
attracting more and more interest since it is considered as a better representation of …
attracting more and more interest since it is considered as a better representation of …