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   Articles with "graph convolution" as a keyword



Memory attention enhanced graph convolution long short‐term memory network for traffic forecasting

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recommendations! Published in 2022 at "International Journal of Intelligent Systems"

DOI: 10.1002/int.22855

Abstract: In recent years, traffic forecasting has gradually attracted attention in data mining because of the increasing availability of large‐scale traffic data. However, it faces substantial challenges of complex temporal‐spatial correlations in traffic. Recent studies mainly… read more here.

Keywords: traffic forecasting; attention; traffic; graph convolution ... See more keywords

Comprehensive Exploration of Target‐specific Ligands Using a Graph Convolution Neural Network

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recommendations! Published in 2019 at "Molecular Informatics"

DOI: 10.1002/minf.201900095

Abstract: Machine learning approaches are widely used to evaluate ligand activities of chemical compounds toward potential target proteins. Especially, exploration of highly selective ligands is important for the development of new drugs with higher safety. One… read more here.

Keywords: convolution neural; graph convolution; exploration; target ... See more keywords
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Near-surface PM2.5 prediction combining the complex network characterization and graph convolution neural network

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recommendations! Published in 2021 at "Neural Computing and Applications"

DOI: 10.1007/s00521-021-06300-3

Abstract: Massive studies focus on the prediction of main pollutants, to improve air quality by revealing the evolution of pollutants. However, existing prediction methods mostly emphasize the fitting analysis of time series, but ignore the spatial… read more here.

Keywords: convolution neural; network; graph convolution; neural network ... See more keywords

Predicting miRNA-disease associations based on lncRNA-miRNA interactions and graph convolution networks

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recommendations! Published in 2022 at "Briefings in bioinformatics"

DOI: 10.1093/bib/bbac495

Abstract: Increasing studies have proved that microRNAs (miRNAs) are critical biomarkers in the development of human complex diseases. Identifying disease-related miRNAs is beneficial to disease prevention, diagnosis and remedy. Based on the assumption that similar miRNAs… read more here.

Keywords: mirna interactions; disease; disease associations; lncrna mirna ... See more keywords

Chrombus-XMBD: a graph convolution model predicting 3D-genome from chromatin features

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recommendations! Published in 2025 at "Briefings in Bioinformatics"

DOI: 10.1093/bib/bbaf183

Abstract: Abstract The 3D conformation of the chromatin is crucial for transcriptional regulation. However, current experimental techniques for detecting the 3D structure of the genome are costly and limited to the biological conditions. Here, we described… read more here.

Keywords: graph convolution; chromatin; convolution model; chromatin features ... See more keywords

Structure-Aware Multi-Hop Graph Convolution for Graph Neural Networks

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3149619

Abstract: We present a spatial graph convolution (GC) to classify signals on a graph. Existing GC methods are limited in using the structural information in the feature space. Furthermore, GCs only aggregate features from one-hop neighboring… read more here.

Keywords: multi hop; neural networks; graph convolution; graph neural ... See more keywords

A Deep Graph Convolution Network-Based Abnormity Detection Model for Largescale Behavioral Data

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3424879

Abstract: It remains important to make abnormity detection from largescale behavioral data of Internet. Existing related approaches mostly failed to employ high-dimensional characteristics of Internet data, which limits the detection effect. To deal with this issue,… read more here.

Keywords: behavioral data; largescale behavioral; network; graph convolution ... See more keywords

Energy Shuttle Graph Convolution for Multimodal Relation Recognition in Videos

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3450312

Abstract: The reasoning of social relationships between characters from visual information can assist people in determining characters’ roles and understanding the interaction patterns of characters in different social contexts. Currently, research has transitioned from static images… read more here.

Keywords: energy; multimodal; recognition; energy shuttle ... See more keywords

Graph Convolution for Large-Scale Graph Node Classification Task Based on Spatial and Frequency Domain Fusion

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3532806

Abstract: In recent years, Graph Neural Networks (GNNs) have achieved significant success in graph-based tasks. However, they still face challenges in complex scenarios, particularly in integrating local and global information, enhancing robustness to noise, and overcoming… read more here.

Keywords: large scale; graph convolution; graph; scale graph ... See more keywords

2-D-to-3-D Lifting Human Pose Estimation Based on Simple Graph Convolution Regression

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recommendations! Published in 2025 at "IEEE Sensors Journal"

DOI: 10.1109/jsen.2025.3596065

Abstract: In 2-D-to-3-D human pose estimation (HPE), the torso connection relationship between joints, which can be seen as important constraint information, is critical to improving the accuracy of 3-D HPE. Previous 3-D HPE methods based on… read more here.

Keywords: convolution; human pose; pose estimation; regression ... See more keywords

ALS Point Cloud Semantic Segmentation Based on Graph Convolution and Transformer With Elevation Attention

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recommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2023.3347224

Abstract: Semantic segmentation of airborne point clouds is crucial for 3D scene reconstruction and remote sensing in surveying applications. Current deep learning methods for point clouds primarily focus on effectively aggregating local neighborhood information. However, they… read more here.

Keywords: point; point cloud; elevation; semantic segmentation ... See more keywords