Essential multi-view graph learning for clustering
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-021-03002-5
Abstract: Multi-view clustering utilizes information from diverse views to improve the performance of clustering. For most existing multi-view spectral clustering methods, information of different views is integrated by pursuing a consensus similarity matrix for clustering. However,… read more here.
Keywords: graph learning; multi view; view; view graph ... See more keywords
EGPDI: identifying protein–DNA binding sites based on multi-view graph embedding fusion
Sign Up to like & getrecommendations! Published in 2024 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbae330
Abstract: Abstract Mechanisms of protein-DNA interactions are involved in a wide range of biological activities and processes. Accurately identifying binding sites between proteins and DNA is crucial for analyzing genetic material, exploring protein functions, and designing… read more here.
Keywords: view graph; binding sites; dna binding; multi view ... See more keywords
Multi-View Graph Neural Architecture Search for Biomedical Entity and Relation Extraction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2022.3205113
Abstract: Recently, graph neural architecture search (GNAS) frameworks have been successfully used to automatically design the optimal neural architectures for many problems such as node classification and graph classification. In the existing GNAS frameworks, the designed… read more here.
Keywords: view; view graph; relation extraction; multi view ... See more keywords
Bidirectional Fusion With Cross-View Graph Filter for Multi-View Clustering
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2024.3413682
Abstract: Most existing multi-view graph clustering models either seek consistent clustering results from similarity matrices and spectral embeddings respectively or follow direct bidirectional integration of them, which ignores the interaction between them. To make up for… read more here.
Keywords: view; fusion cross; view graph; view clustering ... See more keywords
Spatial domain identification method based on multi-view graph convolutional network and contrastive learning
Sign Up to like & getrecommendations! Published in 2025 at "PLOS Computational Biology"
DOI: 10.1371/journal.pcbi.1013369
Abstract: Spatial transcriptomics is a rapidly developing field of single-cell genomics that quantitatively measures gene expression while providing spatial information within tissues. A key challenge in spatial transcriptomics is identifying spatially structured domains, which involves analyzing… read more here.
Keywords: graph convolutional; view graph; domain identification; learning ... See more keywords
Efficient Multi-View Graph Convolutional Network with Self-Attention for Multi-Class Motor Imagery Decoding
Sign Up to like & getrecommendations! Published in 2024 at "Bioengineering"
DOI: 10.3390/bioengineering11090926
Abstract: Research on electroencephalogram-based motor imagery (MI-EEG) can identify the limbs of subjects that generate motor imagination by decoding EEG signals, which is an important issue in the field of brain–computer interface (BCI). Existing deep-learning-based classification… read more here.
Keywords: motor imagery; view graph; multi view; attention ... See more keywords
A Good View for Graph Contrastive Learning
Sign Up to like & getrecommendations! Published in 2024 at "Entropy"
DOI: 10.3390/e26030208
Abstract: Due to the success observed in deep neural networks with contrastive learning, there has been a notable surge in research interest in graph contrastive learning, primarily attributed to its superior performance in graphs with limited… read more here.
Keywords: view; good view; graph contrastive; view graph ... See more keywords