Results 81 to 90 of about 10,205 (230)
PLoS ONEGraph Convolutional Networks (GCNs) perform well in skeleton action recognition tasks, but their pairwise node connections make it difficult to effectively model high-order dependencies between non-adjacent joints.
Dong Chen +4 more
doaj +1 more source
Journal of Time Series Analysis, EarlyView.ABSTRACT Traditional graph representations are insufficient for modelling real‐world phenomena involving multi‐entity interactions, such as collaborative projects or protein complexes, necessitating the use of hypergraphs. While hypergraphs preserve the intrinsic nature of such complex relationships, existing models often overlook temporal evolution in
Xianghe Zhu, Qiwei Yao
wiley +1 more source
International Journal of Imaging Systems and Technology, Volume 36, Issue 4, July 2026.ABSTRACT Gliomas are aggressive brain tumors that require accurate imaging‐based diagnosis, where automated segmentation plays a central role in assessing tumor morphology and guiding treatment decisions. Manual delineation of gliomas is time‐consuming and prone to variability, motivating the use of deep learning to improve consistency and alleviate ...
Cecilia Diana‐Albelda +4 more
wiley +1 more source
Hypergraph coverings and Ramanujan Hypergraphs
, 2023 In this paper we investigate Ramanujan hypergraphs by using hypergraph coverings. We first show that the spectrum of a $k$-fold covering $\bar{H}$ of a connected hypergraph $H$ contains the spectrum of $H$, and that it is the union of the spectrum of $H$ and the spectrum of an incidence-signed hypergraph with $H$ as underlying hypergraph if $k=2 ...
Song, Yi-Min +2 more
openaire +2 more sources
Event-Based Media Enrichment Using an Adaptive Probabilistic Hypergraph Model
, 2015 Nowadays, with the continual development of digital capture technologies and social media services, a vast number of media documents are captured and shared online to help attendees record their experience during events.
Liu, Xueliang +4 more
core +1 more source
CF‐SBERTHet: Collaborative and Textual Knowledge Enhanced Semantic Graphs for Sparse Recommendations
Expert Systems, Volume 43, Issue 7, July 2026.ABSTRACT Modern e‐commerce platforms face a critical challenge: delivering accurate recommendations under extreme user–item interaction sparsity, where textual context remains systematically underutilised. Existing collaborative filtering methods degrade sharply in sparse settings, while semantic approaches fail to capture collaborative patterns ...
He Ma +7 more
wiley +1 more source
Hypergraph neural networks: from signal processing to convolution, u-nets and beyond
Arce, Gonzalo R.Qian, WeiNetwork data has gained significant attention in signal processing and machine learning communities. Existing research mainly centers on simple graphs, which depict only pairwise connections.
Wang, Fuli
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Human Brain Mapping, Volume 47, Issue 8, June 1, 2026.We propose MSSM+, an extension of multiscale structural mapping (MSSM), together with surface supervertex mapping (SSVM) and a Supervertex Vision Transformer (SV‐ViT). Together, these methods exhibited better performance in detecting Alzheimer's disease and less variability across MR vendors than MSSM.
Geonwoo Baek +3 more
wiley +1 more source
, 2011 International audienceHypergraphs are generalization of graphs where each edge (hyperedge) can connect more than two vertices. In simple terms, the hypergraph partitioning problem can be defined as the task of dividing the vertices of hypergraph into two
Uçar, Bora +4 more
core +2 more sources
Two‐Round Ramsey Games on Random Graphs
Random Structures &Algorithms, Volume 68, Issue 3, May 2026.ABSTRACT Motivated by the investigation of sharpness of thresholds for Ramsey properties in random graphs, Friedgut, Kohayakawa, Rödl, Ruciński and Tetali introduced two variants of a single‐player game whose goal is to colour the edges of a random graph, in an online fashion, so as not to create a monochromatic triangle.
Yahav Alon +2 more
wiley +1 more source