Results 251 to 260 of about 58,352 (274)

Multi-way relation-enhanced hypergraph representation learning for anti-cancer drug synergy prediction

Bioinform., 2022
MOTIVATION Drug combinations have exhibited promise in treating cancers with less toxicity and fewer adverse reactions. However, in vitro screening of synergistic drug combinations is time-consuming and labour-intensive because of the combinatorial ...
Xuan Liu, Congzhi Song, Shichao Liu, Menglu Li, Xionghui Zhou, Wen Zhang   +5 more
semanticscholar   +1 more source

Efficient and Effective Attributed Hypergraph Clustering via K-Nearest Neighbor Augmentation

Proc. ACM Manag. Data, 2023
Hypergraphs are an omnipresent data structure used to represent high-order interactions among entities. Given a hypergraph H wherein nodes are associated with attributes, attributed hypergraph clustering (AHC) aims to partition the nodes in H into k ...
Yiran Li, Renchi Yang, Jieming Shi
semanticscholar   +1 more source

Sequence Hypergraphs

2016
We introduce sequence hypergraphs by extending the concept of a directed edge (from simple directed graphs) to hypergraphs. Specifically, every hyperedge of a sequence hypergraph is defined as a sequence of vertices (imagine it as a directed path). Note that this differs substantially from the standard definition of directed hypergraphs.
Böhmovà, Kateřina, Chalopin, Jèrèmie, Mihalàk, Matùš, PROIETTI, GUIDO, Widmayer, Peter   +4 more
openaire   +5 more sources

Hypergraph-enhanced Dual Semi-supervised Graph Classification

International Conference on Machine Learning
In this paper, we study semi-supervised graph classification, which aims at accurately predicting the categories of graphs in scenarios with limited labeled graphs and abundant unlabeled graphs.
Wei Ju, Zhengyan Mao, Siyu Yi, Yifang Qin, Yiyang Gu, Zhiping Xiao, Yifan Wang, Xiao Luo, Ming Zhang   +8 more
semanticscholar   +1 more source

Retrieval-Augmented Hypergraph for Multimodal Social Media Popularity Prediction

Knowledge Discovery and Data Mining
Accurately predicting the popularity of multimodal user-generated content (UGC) is fundamental for many real-world applications such as online advertising and recommendation.
Zhangtao Cheng, Jienan Zhang, Xovee Xu, Goce Trajcevski, Ting Zhong, Fan Zhou   +5 more
semanticscholar   +1 more source

IIS-Hypergraphs

SIAM Journal on Discrete Mathematics, 1996
A subsystem of an inconsistent set of inequalities is an irreducibly inconsistent subsystem (IIS) if it is inconsistent and if it has no inconsistent proper subsystem. Each IIS can be considered the edge of a hypergraph. The paper presents several properties of this special class of hypergraphs (IIS-hypergraphs).
openaire   +1 more source

Hypergraph isomorphism using association hypergraphs

Pattern Recognition Letters, 2019
Abstract Association graphs represent a classical tool to deal with the graph matching problem and recently the idea has been generalized to the case of hypergraphs. In this article, the potential of this approach is explored. The proposed framework uses a class of dynamical systems derived from the Baum-Eagon inequality in order to find the maximum (
Giulia Sandi, Sebastiano Vascon, Marcello Pelillo   +2 more
openaire   +1 more source

Dynamic Hypergraph Structure Learning for Multivariate Time Series Forecasting

IEEE Transactions on Big Data
Multivariate time series forecasting plays an important role in many domain applications, such as air pollution forecasting and traffic forecasting. Modeling the complex dependencies among time series is a key challenging task in multivariate time series
Shun-Kai Wang, Yong Zhang, Xuanqi Lin, Yongli Hu, Qingming Huang, Baocai Yin   +5 more
semanticscholar   +1 more source

T-HyperGNNs: Hypergraph Neural Networks via Tensor Representations

IEEE Transactions on Neural Networks and Learning Systems
Hypergraph neural networks (HyperGNNs) are a family of deep neural networks designed to perform inference on hypergraphs. HyperGNNs follow either a spectral or a spatial approach, in which a convolution or message-passing operation is conducted based on ...
Fuli Wang, K. Pena-Pena, Wei Qian, Gonzalo R. Arce   +3 more
semanticscholar   +1 more source

Hypergraph Neural Network for Skeleton-Based Action Recognition

IEEE Transactions on Image Processing, 2021
Recently, skeleton-based human action recognition has attracted a lot of research attention in the field of computer vision. Graph convolutional networks (GCNs), which model the human body skeletons as spatial-temporal graphs, have shown excellent ...
Xiaoke Hao, Jie Li, Yingchun Guo, Tao Jiang, Ming Yu   +4 more
semanticscholar   +1 more source