Results 31 to 40 of about 1,673 (179)

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

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

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

Learning fuzzy representations for hypergraph node classification

Scientific Reports
As an extension of standard graphs, hypergraphs have demonstrated significant advantages in modeling high-order complex relationships compared with standard graphs. Existing literature has witnessed the great success of hypergraph representation learning
Zhishu Sun, Ruijing Geng, Ge Zhang
doaj   +1 more source

Vehicle Reidentification via Multifeature Hypergraph Fusion

International Journal of Digital Multimedia Broadcasting, 2021
Vehicle reidentification refers to the mission of matching vehicles across nonoverlapping cameras, which is one of the critical problems of the intelligent transportation system.
Wang Li, Zhang Yong, Yuan Wei, Shi Hongxing   +3 more
doaj   +1 more source

Land Use and Land Cover Analysis for Solid Waste Management in NCT Delhi Using Fusion Aware Segformer

Land Degradation &Development, EarlyView.
ABSTRACT The use of Land Use Land Cover (LULC) analysis is a fundamental requirement for urban solid waste management (SWM); however, conventional LULC analysis methods are not well suited to the spatio‐temporal variability, multi‐sensor heterogeneity, and seasonal variations of highly dynamic urban environments.
Rubeena Vohra, Ashish Kumar
wiley   +1 more source

Hypergraph-Mlp: Learning on Hypergraphs Without Message Passing

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Hypergraphs are vital in modelling data with higher-order relations containing more than two entities, gaining prominence in machine learning and signal processing. Many hypergraph neural networks leverage message passing over hypergraph structures to enhance node representation learning, yielding impressive performances in tasks like hypergraph node ...
Tang, B, Chen, S, Dong, X
openaire   +3 more sources

A Novel Full‐Chain Loop Tracking Auditing Framework for Obtaining Audit Evidence With Reasonable Assurance

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT As an attestation engagement, auditing is required to provide reasonable assurance for its conclusions. Traditional auditing has limited capacity to handle unstructured data and is usually based on audit sampling techniques, which can lead to the neglect of important audit evidence during the auditing process and result in a higher audit risk,
Xiaojia Wang, Ziqing Luo, Chaoxu Mu
wiley   +1 more source

Hypergraph Contrastive Learning for both Homophilic and Heterophilic Hypergraphs

CoRR
Hypergraphs, as a generalization of traditional graphs, naturally capture high-order relationships. In recent years, hypergraph neural networks (HNNs) have been widely used to capture complex high-order relationships. However, most existing hypergraph neural network methods inherently rely on the homophily assumption, which often does not hold in real ...
Renchu Guan, Xuyang Li, Yachao Zhang, Wei Pang 0001, Fausto Giunchiglia, Ximing Li 0002, Yonghao Liu 0001, Xiaoyue Feng   +7 more
openaire   +2 more sources

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