Tag: contrastive learning

Researchers have developed meth-SemiCancer2, a deep learning framework that combines domain adaptation and contrastive learning to correct batch effects in ...

Researchers at the Vellore Institute of Technology have built NEXUS-Rec, a five-signal neural recommender that outperforms strong baselines on MovieLens ...

A new shapelet-based soft contrastive learning framework called SCLS improves multivariate time series clustering by avoiding noisy data augmentation and ...

Researchers have developed DES-CMR, an AI model that learns to select and reason over evidence documents end to end while ...

Researchers in China have developed MKMed, a cross-modal AI framework that aligns five types of drug knowledge to overcome the ...

Researchers have developed BHyGNN+, a self-supervised framework that learns representations of heterophilic hypergraphs without labels by contrasting each hypergraph against ...

Researchers in China have developed a dual-path deep learning network that keeps multimodal sentiment analysis accurate even when text, audio ...

A new graph neural network study of spatial transcriptomics finds that attention mechanisms, not elaborate edge features, drive accurate identification ...

A new framework called LLM-H2G fuses large language model semantics with hypergraph contrastive learning to predict herb–disease associations, outperforming existing ...

Researchers have developed a zero-shot classification framework that aligns short, noisy citizen hotline texts with richly described class attributes in ...