Results 191 to 200 of about 246,733 (219)
Dissipative Realization of a Quantum Distance-Based Classifier Using Open Quantum Walks. [PDF]
Entropy (Basel)Maciel PL +3 more
europepmc +1 more source
SMART: spatial multi-omic aggregation using graph neural networks and metric learning. [PDF]
Nat CommunDu Z, Chen Q, Huang W, Chen J, Zheng X.
europepmc +1 more source
Comparative Visual Performance and Optical Stability of Clareon Vivity and TECNIS PureSee EDoF IOLs in Cataract Patients. [PDF]
Clin OphthalmolJeong J, Kim DW, Kim Y, Kim HJ.
europepmc +1 more source
Divergent disruption of brain networks following total and chronic sleep loss: a longitudinal fMRI study. [PDF]
SleepScislewska P +5 more
europepmc +1 more source
ON DISTANCE-$ I $-GRAPHS OF DISTANCE-REGULAR GRAPHS
ON DISTANCE-$ I $-GRAPHS OF DISTANCE-REGULAR GRAPHSopenaire
Some of the next articles are maybe not open access.
Related searches:
Related searches:
International Journal of Computational Geometry & Applications, 1991
A new necessary condition for a graph G to be the visibility graph of a simple polygon is given: each 3-connected component of G must have a vertex ordering in which every vertex is adjacent to a previous 3-clique. This property is used to give an algorithm for the distance visibility graph problem: given an edge-weighted graph G, is it the visibility
Collette R. Coullard, Anna Lubiw
openaire +1 more source
A new necessary condition for a graph G to be the visibility graph of a simple polygon is given: each 3-connected component of G must have a vertex ordering in which every vertex is adjacent to a previous 3-clique. This property is used to give an algorithm for the distance visibility graph problem: given an edge-weighted graph G, is it the visibility
Collette R. Coullard, Anna Lubiw
openaire +1 more source
2020
In this article, our ultimate goal is to transform a graph’s adjacency matrix into a distance matrix. Because cluster density is not observable prior to the actual clustering, our goal is to find a distance whose pairwise minimization will lead to densely connected clusters.
Pierre Miasnikof +4 more
openaire +1 more source
In this article, our ultimate goal is to transform a graph’s adjacency matrix into a distance matrix. Because cluster density is not observable prior to the actual clustering, our goal is to find a distance whose pairwise minimization will lead to densely connected clusters.
Pierre Miasnikof +4 more
openaire +1 more source
Distance Graphs on the Integers
Combinatorics, Probability and Computing, 2005We consider several extremal problems concerning representations of graphs as distance graphs on the integers. Given a graph $G=(V,E)$, we wish to find an injective function $\phi:V\to{\mathbb Z}^+=\{1,2,\dots\}$ and a set ${\mathcal D}\subset{\mathbb Z}^+$ such that $\{u,v\}\in E$ if and only if $|\phi(u)-\phi(v)|\in{\mathcal D}$. Let $s(n)$ be the
Mike Ferrara +2 more
openaire +2 more sources
Two Laplacians for the distance matrix of a graph
Linear Algebra and Its Applications, 2013Mustapha Aouchiche, Pierre Hansen
exaly