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   Articles with "graph structure" as a keyword



Dynamic graph structure evolution for node classification with missing attributes

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-09840-z

Abstract: Graph neural networks (GNN) have achieved remarkable success in various domains, yet incomplete node attribute data can significantly impair their performance. Graph completion learning (GCL) methods have been developed to address this issue, aiming to… read more here.

Keywords: classification missing; structure; node classification; missing attributes ... See more keywords

Attention-guided graph structure learning network for EEG-enabled auditory attention detection

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recommendations! Published in 2024 at "Journal of Neural Engineering"

DOI: 10.1088/1741-2552/ad4f1a

Abstract: Objective: Decoding auditory attention from brain signals is essential for the development of neuro-steered hearing aids. This study aims to overcome the challenges of extracting discriminative feature representations from electroencephalography (EEG) signals for auditory attention… read more here.

Keywords: auditory attention; attention; attention detection; graph structure ... See more keywords

A comfortable graph structure for Grover walk

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recommendations! Published in 2022 at "Journal of Physics A: Mathematical and Theoretical"

DOI: 10.1088/1751-8121/acd735

Abstract: We consider a Grover walk model on a finite internal graph, which is connected with a finite number of semi-infinite length paths and receives the alternative inflows along these paths at each time step. After… read more here.

Keywords: grover walk; internal graph; graph; comfortable graph ... See more keywords

Learning representations for gene ontology terms by jointly encoding graph structure and textual node descriptors

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recommendations! Published in 2022 at "Briefings in bioinformatics"

DOI: 10.1093/bib/bbac318

Abstract: Measuring the semantic similarity between Gene Ontology (GO) terms is a fundamental step in numerous functional bioinformatics applications. To fully exploit the metadata of GO terms, word embedding-based methods have been proposed recently to map… read more here.

Keywords: structure; encoding graph; ontology; gene ontology ... See more keywords

Impacts of graph structure on the computational properties of oscillator Ising machines.

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recommendations! Published in 2025 at "Physical review. E"

DOI: 10.1103/physreve.111.044211

Abstract: Many combinatorial optimization problems (COPs) can be mapped to Ising Hamiltonians. Oscillator Ising machines (OIMs) are built to minimize the Ising Hamiltonians, thereby indirectly solving the COPs. Specifically, the dynamics of an OIM evolve in… read more here.

Keywords: oscillator ising; ising machines; impacts graph; structure ... See more keywords

Generative Service Provisioning for IoT Devices Using Line Graph Structure

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3244890

Abstract: A service subgraph helps Internet-of-Things devices access resources in a dynamic Internet-of-Things device network. We propose a service subgraph generation method for Internet-of-Things device networks. Service subgraph generation aims to find more capable neighboring Internet-of-Things… read more here.

Keywords: service provisioning; service subgraph; service; line graph ... See more keywords

RumorGraphXplainer: Do Structures Really Matter in Rumor Detection

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recommendations! Published in 2024 at "IEEE Transactions on Computational Social Systems"

DOI: 10.1109/tcss.2024.3378065

Abstract: The rise of social media has enabled individuals to rapidly share information, including rumors, which can have significant impacts on various domains. Traditional approaches to rumor control are impractical for social media platforms due to… read more here.

Keywords: detection; graph structure; rumor detection; propagation dispersion ... See more keywords

Hyperspectral Image Classification Based on Superpixel Feature Subdivision and Adaptive Graph Structure

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recommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2022.3153446

Abstract: The graph-based hyperspectral image classification (HSIC) method has attracted wide attention because it can extract information with a non-Euclidean structure. Many graph-based HSIC works have achieved good results, but unresolved technical issues remain. For example,… read more here.

Keywords: structure; graph structure; classification; graph ... See more keywords

GraphMamba: An Efficient Graph Structure Learning Vision Mamba for Hyperspectral Image Classification

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recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2024.3493101

Abstract: Efficient extraction of spectral sequences and geospatial information is crucial in hyperspectral image (HSI) classification. Recurrent neural networks (RNNs) and Transformers excel in capturing long-range spectral features, while convolutional neural networks (CNNs) excel in aggregating… read more here.

Keywords: classification; information; hyperspectral image; graphmamba efficient ... See more keywords

Fusion Graph Structure Learning-Based Multivariate Time Series Anomaly Detection With Structured Prior Knowledge

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recommendations! Published in 2024 at "IEEE Transactions on Information Forensics and Security"

DOI: 10.1109/tifs.2024.3459631

Abstract: Multivariate time series anomaly detection (MTSAD) plays a crucial role in the Internet of Things (IoT) to identify device malfunction or system attacks. Graph neural networks (GNN) are widely applied in MTSAD to capture the… read more here.

Keywords: time series; graph structure; graph; anomaly detection ... See more keywords

Dual-Graph Collaboration: Bidirectional Fusion Graph Convolution Network for Structure Multidefect Positioning and Assessment

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recommendations! Published in 2024 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2024.3435441

Abstract: Graph convolution network can extract structural multidefect information well, and has been widely concerned in the field of structural damage detection. However, it is difficult to locate and evaluate defects of different sizes only using… read more here.

Keywords: structure; convolution network; dual graph; graph convolution ... See more keywords