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Found 6 papers, 0 papers with code
AGHINT: Attribute-Guided Representation Learning on Heterogeneous Information Networks with Transformer
Recently, heterogeneous graph neural networks (HGNNs) have achieved impressive success in representation learning by capturing long-range dependencies and heterogeneity at the node level.
Type-based Neural Link Prediction Adapter for Complex Query Answering
Answering complex logical queries on incomplete knowledge graphs (KGs) is a fundamental and challenging task in multi-hop reasoning.
RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine
Traditional Chinese medicine (TCM) prescription is the most critical form of TCM treatment, and uncovering the complex nonlinear relationship between symptoms and TCM is of great significance for clinical practice and assisting physicians in diagnosis and treatment.
MultiModal-Learning for Predicting Molecular Properties: A Framework Based on Image and Graph Structures
An effective representation of drug molecules emerges as a pivotal component in this pursuit.
ACDNet: Attention-guided Collaborative Decision Network for Effective Medication Recommendation
ACDNet also employs a collaborative decision framework, utilizing the similarity between medication records and medicine representation to facilitate the recommendation process.
Hybrid Attentional Memory Network for Computational drug repositioning
Then a variant version of the autoencoder is used to extract the latent factor of drugs and diseases to capture the overall information shared by a majority of drug-disease associations.
