Results 51 to 60 of about 2,251 (141)

Counting Independent Sets in Percolated Graphs via the Ising Model

open access: yesRandom Structures &Algorithms, Volume 68, Issue 1, January 2026.
ABSTRACT Given a graph G$$ G $$, we form a random subgraph Gp$$ {G}_p $$ by including each edge of G$$ G $$ independently with probability p$$ p $$. We provide an asymptotic expansion of the expected number of independent sets in random subgraphs of regular bipartite graphs satisfying certain vertex‐isoperimetric properties, extending the work of ...
Anna Geisler   +3 more
wiley   +1 more source

Hypergraph Learning with Line Expansion

open access: yes, 2020
Previous hypergraph expansions are solely carried out on either vertex level or hyperedge level, thereby missing the symmetric nature of data co-occurrence, and resulting in information loss.
Abdelzaher, Tarek   +3 more
core  

A Hybrid Deep Learning Framework for Early Detection of Ovarian Cancer Using Ultrasound and MRI Images on a Secure Cloud Platform

open access: yesComplexity, Volume 2026, Issue 1, 2026.
Ovarian cancer continues to pose a major diagnostic challenge, as early‐stage disease often presents with subtle and heterogeneous imaging characteristics that limit the effectiveness of single‐modality analysis. In response to this challenge, this study proposes a novel hybrid deep learning framework for the early detection and classification of ...
Umesh Kumar Lilhore   +9 more
wiley   +1 more source

Unifying Invariant and Variant Knowledge With Dual‐Hypergraph Contrastive Evolution for Temporal Knowledge Graph Reasoning

open access: yesInternational Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
Temporal knowledge graph reasoning (TKGR) excels at inferring missing event‐centric facts within a timeline, thereby mitigating the inherent incompleteness of real‐world data. Existing TKGR methods predominantly exploit intrasnapshot structural patterns and intersnapshot temporal dependencies.
Fei Chen   +7 more
wiley   +1 more source

Phase transitions in Delaunay Potts models

open access: yes, 2015
We establish phase transitions for classes of continuum Delaunay multi-type particle systems (continuum Potts models) with infinite range repulsive interaction between particles of different type.
Adams, Stefan, Eyers, Michael
core   +1 more source

Uncovering Regulatory Networks Through Residual Graph Learning of circRNA–miRNA Interactions

open access: yesInternational Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
Circular RNAs (circRNAs) and microRNAs (miRNAs) are key regulators of gene expression, and their interactions are involved in many biological processes and diseases. Nevertheless, the experimental validation of circRNA–miRNA interactions (CMIs) remains challenging due to resource and technical constraints; therefore, robust computational models are ...
Murtada K. Elbashir   +3 more
wiley   +1 more source

A note on 2-subset-regular self-complementary 3-uniform hypergraphs

open access: yes, 2008
We show that a 2-subset-regular self-complementary 3-uniform hypergraph with $n$ vertices exists if and only if $n\ge 6$ and $n$ is congruent to 2 modulo 4.
Knor, Martin, Potocnik, Primoz
openaire   +2 more sources

Overgroups of the Automorphism Group of the Rado Graph

open access: yes, 2012
We are interested in overgroups of the automorphism group of the Rado graph. One class of such overgroups is completely understood; this is the class of reducts.
Cameron, Peter   +4 more
core   +2 more sources

The history of degenerate (bipartite) extremal graph problems [PDF]

open access: yes, 2013
This paper is a survey on Extremal Graph Theory, primarily focusing on the case when one of the excluded graphs is bipartite. On one hand we give an introduction to this field and also describe many important results, methods, problems, and constructions.
A. A. Razborov   +198 more
core   +1 more source

CoRoFR: Community Detection of Feature Graph Improves Feature Selection Using Robust Fuzzy Rough Set

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 12, December 2025.
In machine learning, features often function as communities in many tasks, especially in medicine. However, existing feature selection methods struggle to mine feature collaborations, which can boost predictive performance. Moreover, they are noise‐sensitive, leading to suboptimal feature selection and accuracy degradation.
Duanyang Feng   +4 more
wiley   +1 more source

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