Results 81 to 90 of about 2,218,762 (336)
Random walks with long-range steps generated by functions of Laplacian matrices
, 2018 In this paper, we explore different Markovian random walk strategies on networks with transition probabilities between nodes defined in terms of functions of the Laplacian matrix.
Collet, B. A. +4 more
core +1 more source
On minors of the compound matrix of a Laplacian
Linear Algebra and its Applications, 2013 Abstract Let L be an n × n matrix with zero row and column sums, n ⩾ 3 . We obtain a formula for any minor of the ( n − 2 ) -th compound of L. An application to counting spanning trees extending a given forest is given.
openaire +2 more sources
Linear Software Models: Modularity Analysis by the Laplacian Matrix
ICSOFT-PT, 2016 We have recently shown that one can obtain the number and sizes of modules of a software system from the eigenvectors of the Modularity Matrix weighted by an affinity matrix.
I. Exman, Rawi Sakhnini
semanticscholar +1 more source
Reconstructing Three‐Dimensional Optical Anisotropy with Tomographic Müller‐Polarimetric Microscopy
Advanced Science, EarlyView.Tomographic Müller polarimetric microscopy is a novel imaging technique that resolves 3D birefringent properties of bulky samples, unveiling hierarchical nanostructures at microscopic resolution. Based on incoherent visible‐light polarimetry, it achieves experimental simplicity by eliminating phase measurements.
Yang Chen +4 more
wiley +1 more source
Using twins and scaling to construct cospectral graphs for the normalized Laplacian
, 2014 The spectrum of the normalized Laplacian matrix cannot determine the number of edges in a graph, however finding constructions of cospectral graphs with differing number of edges has been elusive.
Steve Butler, Steve Butler
core +2 more sources
CeiTEA: Adaptive Hierarchy of Single Cells with Topological Entropy
Advanced Science, EarlyView.CeiTEA, a novel hierarchical clustering algorithm based on topological entropy, effectively captures complex structures underlying data. By constructing an adaptive multi‐nary partition tree, CeiTEA reveals hierarchical structures and local diversifications, outperforming existing methods in clustering accuracy and consistency and providing the ...
Bowen Tan +3 more
wiley +1 more source
Communications in Advanced Mathematical Sciences, 2018 The signless Laplacian eigenvalues of a graph $G$ are eigenvalues of the matrix $Q(G) = D(G) + A(G)$, where $D(G)$ is the diagonal matrix of the degrees of the vertices in $G$ and $A(G)$ is the adjacency matrix of $G$.
Rao Li
doaj +1 more source
NFFT Meets Krylov Methods: Fast Matrix-Vector Products for the Graph Laplacian of Fully Connected Networks [PDF]
Frontiers in Applied Mathematics and Statistics, 2018 The graph Laplacian is a standard tool in data science, machine learning, and image processing. The corresponding matrix inherits the complex structure of the underlying network and is in certain applications densely populated.
Dominik Alfke +3 more
semanticscholar +1 more source
Advanced Science, EarlyView.This study developed an unsupervised radiomics system integrating CT imaging and multi‐omics data to stratify clear cell renal cell carcinoma into two subtypes with distinct clinical outcomes. Cluster 1 showed lower recurrence risk and active immunity, while Cluster 2 exhibited higher recurrence risk, enriched VHL/KDM5C mutations, immunosuppressive ...
Yusheng Guo +14 more
wiley +1 more source
Multi‐view subspace clustering with incomplete graph information
IET Computer Vision, EarlyView., 2022 Abstract The core of multi‐view clustering is how to exploit the shared and specific information of multi‐view data properly. The data missing and incompleteness bring great challenges to multi‐view clustering. In this paper, we propose an innovative multi‐view subspace clustering method with incomplete graph information, so‐called incomplete multiple ...
Xiaxia He +5 more
wiley +1 more source