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Everything about Multidimensional network
Networks with multiple kinds of relations
In network theory, multidimensional networks, a special type of multilayer network, are networks with multiple kinds of relations. Increasingly sophisticated attempts to model real-world systems as multidimensional networks have yielded valuable insight in the fields of social network analysis, economics, urban and international transport, ecology, psychology, medicine, biology, commerce, climatology, physics, computational neuroscience, operations management, and finance. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Multidimensional networkA 5-minute orientation
- Skim a recent paper: Epileptic seizure prediction via multidimensional transformer and recurrent neural network fusionInfluential work since 2022
- Pick up a classic book: Representing stages of learning in neural network systems using multidimensional scalingThe most-reprinted book on the subject
- Read the landmark paper: Olfactory network dynamics and the coding of multidimensional signalsCited 635 times
- Go sideways: AssortativityA closely related topic
- Go sideways: Tensor–vector–scalar gravityA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Olfactory network dynamics and the coding of multidimensional signals
Social Network Types Among Older Adults: A Multidimensional Approach
Co-created value: Multidimensional scale and nomological network
Multidimensional data in multidimensional scaling using the analytic network process
Multidimensional Social Network in the Social Recommender System
Multidimensional context-aware social network architecture for mobile crowdsensing
Augmented Multidimensional Convolutional Neural Network for Industrial Soft Sensing
T-cell activation: a multidimensional signaling network
🆕 Influential since 2022
Epileptic seizure prediction via multidimensional transformer and recurrent neural network fusion
A Novel Multidimensional Domain Deep Learning Network for SAR Ship Detection
Multidimensional Fusion Network for Multispectral Object Detection
Multidimensional Prototype Refactor Enhanced Network for Few-Shot Action Recognition
MCLNet: An multidimensional convolutional lightweight network for gastric histopathology image classification
đź“š Books worth reading
- 📕Representing stages of learning in neural network systems using multidimensional scalingDavid P. Crismond, Harvard University. Graduate School of Education · 1993
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
- Assortativity Assortativity, or assortative mixing, is a preference for a network's nodes to attach to others that are similar in some way. Though the specific measure…
- Tensor–vector–scalar gravity Tensor–vector–scalar gravity (TeVeS), developed by Jacob Bekenstein in 2004, is a relativistic generalization of Mordehai Milgrom's Modified Newtonian…
- Holst action In the field of theoretical physics, the Holst action is an equivalent formulation of the Palatini action for General Relativity (GR) in terms of vierbeins…
- Infinite derivative gravity Infinite derivative gravity is a theory of gravity which attempts to remove cosmological and black hole singularities by adding extra terms to the Einstein–Hilb…
- Network entropy In network science, the network entropy is a disorder measure derived from information theory to describe the level of randomness and the amount of information…
- Google matrix A Google matrix is a particular stochastic matrix that is used by Google's PageRank algorithm. The matrix represents a graph with edges representing links…
- Scalar–tensor–vector gravity Scalar–tensor–vector gravity (STVG) is a modified theory of gravity developed by John Moffat, a researcher at the Perimeter Institute for Theoretical Physics…
- Bimetric gravity Bimetric gravity or bigravity refers to two different classes of theories. The first class of theories relies on modified mathematical theories of gravity…