This paper proposes BioWave, a multi-hop diffusion-wavelet model that learns both structural and semantic representations for accurate CMI prediction and achieves superior performance compared to state-of-the-art baselines, particularly in zero-shot settings.
Mengmeng Wei, Lei Wang, Peng-Wei Hu et al.· Proceedings of the 32nd ACM...· 0 citations
Continual spatio-temporal forecasting supports traffic management and environmental monitoring under evolving dynamics and expanding sensor networks. However, conventional graph-based continual learning methods tie forecasting representations to the current sensor layout, so sensor expansion can alter the representatio...
Le-Wei Xie, Hao-Yu Zhang, Jia-Jun Zhou et al.· 0 citations
ScGraphTrans, a graph neural network framework that integrates functional state pseudo-labels, graph structure learning, and graph domain adaptation to improve both cell type annotation and communication inference, is proposed, offering insights into biomarker discovery and therapeutic strategies.
Yue-Chao Li, Hai-Ru You, Meng-Chao Wei et al.· IEEE transactions on computa...· 0 citations
Experiments on three cross-patient scRNA-seq data sets demonstrate that PathoGraph achieves stable annotation performance across 32 directed reference-to-query transfer tasks, showing competitive and stable performance compared with representative marker-based, correlation-based, and model-based annotation methods.
Yue C. Li, Mengmeng Wei, Xinfei Wang et al.· Journal of Chemical Informat...· 0 citations
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