Results 31 to 40 of about 58,352 (274)
CHGNN: A Semi-Supervised Contrastive Hypergraph Learning Network [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2023 Hypergraphs can model higher-order relationships among data objects that are found in applications such as social networks and bioinformatics. However, recent studies on hypergraph learning that extend graph convolutional networks to hypergraphs cannot ...
Yumeng Song +6 more
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Automatic Software Module Partition Based on Hypergraph Model [PDF]
Jisuanji gongcheng, 2016 This paper applies the hypergraph model to design automatic software module partition algorithm.Under the hypergraph modeling,each significant class extracted from the source codes of an analyzing software system is abstracted as a vertex of a hypergraph,
WEI Xiaofeng,HU Jicheng,LUO Yong’en
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Trends in Biotechnology, 2014 Signaling pathways function as the information-passing mechanisms of cells. A number of databases with extensive manual curation represent the current knowledge base for signaling pathways. These databases motivate the development of computational approaches for prediction and analysis.
Anna, Ritz +4 more
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The k-annihilating-ideal hypergraph of commutative ring
AKCE International Journal of Graphs and Combinatorics, 2019 The concept of the annihilating-ideal graph of a commutative ring was introduced by Behboodi et. al in 2011. In this paper, we extend this concept to the hypergraph for which we define an algebraic structure called k-annihilating-ideal of a commutative ...
K. Selvakumar, V. Ramanathan
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Nonintersecting Ryser Hypergraphs [PDF]
SIAM Journal on Discrete Mathematics, 2020 8 pages, some corrections in the proof of Lemma 3.6, added more explanation in the appendix, and other minor ...
Bishnoi A., Pepe V.
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Be More with Less: Hypergraph Attention Networks for Inductive Text Classification [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 Text classification is a critical research topic with broad applications in natural language processing. Recently, graph neural networks (GNNs) have received increasing attention in the research community and demonstrated their promising results on this ...
Kaize Ding +4 more
semanticscholar +1 more source
Multi-order hypergraph convolutional networks integrated with self-supervised learning
Complex & Intelligent Systems, 2023 Hypergraphs, as a powerful representation of information, effectively and naturally depict complex and non-pair-wise relationships in the real world. Hypergraph representation learning is useful for exploring complex relationships implicit in hypergraphs.
Jiahao Huang +5 more
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The Electronic Journal of Combinatorics, 2010 The notion of pattern hypergraph provides a unified view of several previously studied coloring concepts. A pattern hypergraph $H$ is a hypergraph where each edge is assigned a type $\Pi_i$ that determines which of possible colorings of the edge are proper. A vertex coloring of $H$ is proper if it is proper for every edge.
Dvořák, Zdeněk +3 more
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Hyper-YOLO: When Visual Object Detection Meets Hypergraph Computation [PDF]
IEEE Transactions on Pattern Analysis and Machine IntelligenceWe introduce Hyper-YOLO, a new object detection method that integrates hypergraph computations to capture the complex high-order correlations among visual features.
Yifan Feng +8 more
semanticscholar +1 more source
Oriented hypergraphs: Balanceability
Discrete Mathematics, 2022 An oriented hypergraph is an oriented incidence structure that extends the concepts of signed graphs, balanced hypergraphs, and balanced matrices. We introduce hypergraphic structures and techniques that generalize the circuit classification of the signed graphic frame matroid to any oriented hypergraphic incidence matrix via its locally-signed-graphic
Lucas J. Rusnak +4 more
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