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Everything about Distance matrix
Square matrix containing the distances between elements in a set
In mathematics, computer science and especially graph theory, a distance matrix is a square matrix containing the distances, taken pairwise, between the elements of a set. Depending upon the application involved, the "distance" being used to define this matrix may or may not be a metric. If there are N elements, this matrix will have size N×N. In graph-theoretic applications, the elements are usually referred to as points, nodes or vertices. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Distance matrixA 5-minute orientation
- Skim a recent paper: Every nonsingular spherical Euclidean distance matrix is a resistance distance matrixInfluential work since 2022
- Pick up a classic book: Linear Algebra with ApplicationsThe most-reprinted book on the subject
- Read the landmark paper: FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance MatrixCited 5,411 times
- Go sideways: Distance matrices in phylogenyA closely related topic
- Go sideways: T-REX (web server)A closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix
Information theory, distance matrix, and molecular branching
Distance matrix polynomials of trees
The distance matrix in chemistry
On the distance matrix of a tree
The Euclidian Distance Matrix Completion Problem
The generalized distance matrix
Matrix versions of the Hellinger distance
🆕 Influential since 2022
Every nonsingular spherical Euclidean distance matrix is a resistance distance matrix
Learning matrix factorization with scalable distance metric and regularizer
Euclidean Distance Matrix-Based Rapid Fault Detection and Exclusion
Distance Matrix and Markov Chain Based Sensor Localization in WSN
A Euclidean Distance Matrix Model for Convex Clustering
📚 Books worth reading
Linear Algebra with ApplicationsGareth Williams · 1984
Neural Information ProcessingTingwen Huang · 2012
Using MPIWilliam Gropp, Ewing Lusk · 1994
Statistical Atlases and Computational Models of the Heart. Imaging and Modelling ChallengesOscar Camara · 2012
3D math primer for graphics and game developmentFletcher Dunn · 2002
The trainer's handbookKaren Lawson · 2006
The Elements of Statistical LearningTrevor Hastie, Robert Tibshirani · 2001
Graph theory with applications to engineering and computer scienceNarsingh Deo, Narsingh Deo · 1974
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Distance matrices in phylogeny Distance matrices are used in phylogeny as non-parametric distance methods and were originally applied to phenetic data using a matrix of pairwise distances…
- T-REX (web server) T-REX (Tree and Reticulogram Reconstruction) is a freely available web server, developed at the department of Computer Science of the Université du Québec…
- Computational phylogenetics Computational phylogenetics, phylogeny inference, or phylogenetic inference focuses on computational and optimization algorithms, heuristics, and approaches…
- UPGMA UPGMA (unweighted pair group method with arithmetic mean) is a simple agglomerative (bottom-up) hierarchical clustering method. It also has a weighted…
- Neighbor joining In bioinformatics, neighbor joining is a bottom-up (agglomerative) clustering method for the creation of phylogenetic trees, created by Naruya Saitou and…
- Single-linkage clustering In statistics, single-linkage clustering is one of several methods of hierarchical clustering. It is based on grouping clusters in bottom-up fashion (agglomerat…
- Similarity measure In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity…
- Isomap Isomap is a nonlinear dimensionality reduction method. It is one of several widely used low-dimensional embedding methods. Isomap is used for computing…