Results 41 to 50 of about 9,987 (195)

EasyHypergraph: an open-source software for fast and memory-saving analysis and learning of higher-order networks

Humanities & Social Sciences Communications
Higher-order relationships exist widely across different disciplines. In the realm of real-world systems, significant interactions involving multiple entities are common.
Bodian Ye, Min Gao, Xiu-Xiu Zhan, Xinlei He, Zi-Ke Zhang, Qingyuan Gong, Xin Wang, Yang Chen   +7 more
doaj   +1 more source

Android Malware Detection Based on Hypergraph Neural Networks

Applied Sciences, 2023
Android has been the most widely used operating system for mobile phones over the past few years. Malicious attacks against android are a major privacy and security concern. Malware detection techniques for android applications are therefore significant.
Dehua Zhang, Xiangbo Wu, Erlu He, Xiaobo Guo, Xiaopeng Yang, Ruibo Li, Hao Li   +6 more
doaj   +1 more source

Hypergraph Learning with Hyperedge Expansion [PDF]

, 2012
We propose a new formulation called hyperedge expansion (HE) for hypergraph learning. The HE expansion transforms the hypergraph into a directed graph on the hyperedge level. Compared to the existing works (e.g. star expansion or normalized hypergraph cut), the learning results with HE expansion would be less sensitive to the vertex distribution among ...
Li Pu, Boi Faltings
openaire   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Latent Semantic Learning with Structured Sparse Representation for Human Action Recognition

, 2011
This paper proposes a novel latent semantic learning method for extracting high-level features (i.e. latent semantics) from a large vocabulary of abundant mid-level features (i.e.
Balasubramanian, Belkin, Blei, Cheng, Donoho, Hofmann, Jenatton, Lafon, Liu, Lu, Niebles, Olshausen, Parameswaran, Tibshirani, Turaga, Wang, Wright, Yan, Yuxin Peng, Zhiwu Lu   +19 more
core   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

Single‐Cell and Spatial Omics: Methods and Applications

MedComm, Volume 7, Issue 4, April 2026.
Systematically summarized the breakthrough sequencing technologies and computational methods for single‐cell and spatial omics across multiple omics layers, including genome, epigenome, transcriptome, proteome, and metabolome. State‐of‐the‐art methods for multi‐omics integration, cross‐modal integration, and cross‐scale integration were reviewed, with ...
Xiaoping Cen, Xiaolan Huang, Enjin Deng, Xue Gong, Na Tan, Jifeng Ye, Yin Wang, Roland Eils, Qun Luo, Yixue Li, Fangfang Qu   +10 more
wiley   +1 more source

Self-Supervised Hypergraph Learning for Enhanced Multimodal Representation

IEEE Access
Hypergraph neural networks have gained substantial popularity in capturing complex correlations between data items in multimodal datasets. In this study, we propose a novel approach called the self-supervised hypergraph learning (SHL) framework that ...
Hongji Shu, Chaojun Meng, Pasquale De Meo, Qing Wang, Jia Zhu   +4 more
doaj   +1 more source

A Universal Meta‐Heuristic Framework for Influence Maximisation in Hypergraphs

CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 396-410, April 2026.
ABSTRACT Influence maximisation (IM) aims to select a small number of nodes that are able to maximise their influence in a network and covers a wide range of applications. Despite numerous attempts to provide effective solutions in simple networks, higher‐order interactions between entities in various real‐world systems are usually not taken into ...
Ming Xie, Chuang Liu, Yang Chen, Zi‐Ke Zhang, Xiaoyang Liu, Xiu‐Xiu Zhan   +5 more
wiley   +1 more source

NE-DCHL: Nonlinear Enhanced Disentangled Contrastive Hypergraph Learning for Next Point-of-Interest Recommendation

Information
Next Point-of-Interest (POI) recommendation is a crucial task in personalized location-based services, aiming to predict the next POI that a user might visit based on their historical trajectories. Although sequence models and Graph Neural Networks (GNNs)
Hongwei Zhang, Guolong Wang, Xiaofeng Yan   +2 more
doaj   +1 more source