Fuzzy multi-view learning (FMVL) integrates fuzzy modeling with multi-view learning to address uncertainty, incompleteness, heterogeneity, and unequal contributions across multiple views. Despite growing interest, existing studies remain dispersed across different fuzzy mechanisms, learning paradigms, and data settings...
An-Dong Li, Hai-Bo Liu, Fu-Ping Hu et al.· Symmetry· 0 citations
A novel Shared-Specific Multi-view Graph Convolutional Network (SSMGCN) is proposed, which consistently outperforms existing methods in spatial domain identification and its unified embedding supports downstream tasks such as cell-type annotation, spatial localization, and functional analysis, providing a robust founda...
Wei Zhang, Dan-Yang Dong, Bang-Yi Zhang et al.· IEEE transactions on computa...· 0 citations
The enzyme kinetic parameters, including the turnover number, Michaelis constant, and inhibition constant, are key metrics for assessing catalytic performance. Although deep learning models have recently incorporated multimodal information from enzymes and substrates to predict these parameters, several obstacles still...
Cheng-Hao Zhu, Wei-Ping Ding, Wei Zhang et al.· Journal of Chemical Informat...· 0 citations
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