Results 51 to 60 of about 59,275 (246)
Induced subgraphs of hypercubes
European Journal of Combinatorics, 2013 Let $Q_k$ denote the $k$-dimensional hypercube on $2^k$ vertices. A vertex in a subgraph of $Q_k$ is {\em full} if its degree is $k$. We apply the Kruskal-Katona Theorem to compute the maximum number of full vertices an induced subgraph on $n\leq 2^k$ vertices of $Q_k$ can have, as a function of $k$ and $n$. This is then used to determine $\min(\max(|V(
openaire +3 more sources
Maximum Induced Subgraph of an Augmented Cube
, 2014 Let maxζG(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. The n-dimensional augmented cube, denoted as AQn, a variation of the hypercube, possesses some properties superior to those of the hypercube. We study the cases when G is the augmented cube AQn.
Meng-Jou Chien +2 more
openaire +1 more source
Efficient Enumeration of Induced Subtrees in a K-Degenerate Graph
, 2014 In this paper, we address the problem of enumerating all induced subtrees in an input k-degenerate graph, where an induced subtree is an acyclic and connected induced subgraph.
A Shioura +7 more
core +1 more source
Robust Densest Subgraph Discovery
, 2018 Dense subgraph discovery is an important primitive in graph mining, which has a wide variety of applications in diverse domains. In the densest subgraph problem, given an undirected graph $G=(V,E)$ with an edge-weight vector $w=(w_e)_{e\in E}$, we aim to
Miyauchi, Atsushi, Takeda, Akiko
core +1 more source
Multiscale Cell–Cell Interactive Spatial Transcriptomics Analysis
Advanced Science, EarlyView.In this study, we present the MultiScale Cell‐Cell Interactive Spatial Transcriptomics Analysis method, which unites the strengths of spatially resolved deep learning techniques with a topological representation of multi‐scale cell‐cell similarity relations.
Sean Cottrell, Guo‐Wei Wei
wiley +1 more source
Motif-role-fingerprints: the building-blocks of motifs, clustering-coefficients and transitivities in directed networks. [PDF]
PLoS ONE, 2014 Complex networks are frequently characterized by metrics for which particular subgraphs are counted. One statistic from this category, which we refer to as motif-role fingerprints, differs from global subgraph counts in that the number of subgraphs in ...
Mark D McDonnell +5 more
doaj +1 more source
Advanced Science, EarlyView.Real‐time and accurate monitoring of battery surface temperature is widely recognized as essential for ensuring operational safety. By synergistically combining high‐resolution sensing‐interrogation systems, optimized DOFS deployment scheme, and intelligent reconstruction algorithms, this study achieves full‐range and high‐fidelity temperature field ...
Yuhao Zhu +6 more
wiley +1 more source
In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR
Advanced Intelligent Discovery, EarlyView.Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley +1 more source
Advanced Intelligent Systems, EarlyView.R‐APEX is a knowledge graph platform developed to investigate how air pollutants such as particularly fine particulate matter (PM2.5) affect human health. By integrating large‐scale biomedical data and using machine learning, it reveals pollutant–gene–disease associations.
Zhixing Zhu +7 more
wiley +1 more source
Maximum common subgraph: some upper bound and lower bound results
BMC Bioinformatics, 2006 Background Structure matching plays an important part in understanding the functional role of biological structures. Bioinformatics assists in this effort by reformulating this process into a problem of finding a maximum common subgraph between graphical
Jennings Steven F +2 more
doaj +1 more source