Area of research
Artificial Intelligence · Information Systems
Research interest
Research focused on Embedding and Graph, with related work in Relation (database), Knowledge graph, Artificial intelligence. Notable publications include 'Application of Bayesian networks to generate synthetic health data', 'ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding', and 'TARGAT: A Time-Aware Relational Graph Attention Model for Temporal Knowledge Graph Embedding'.
MiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysis
Bioinformatics Course Reform Through Projects Integrating History, Theory, and Practice
Efficient cluster-guided key timestamp discovery for temporal knowledge graph completion
One Subgraph for All: Efficient Reasoning on Opening Subgraphs for Inductive Knowledge Graph Completion
Learning dual disentangled representation with self-supervision for temporal knowledge graph reasoning
TARGAT: A Time-Aware Relational Graph Attention Model for Temporal Knowledge Graph Embedding
Incorporating global–local neighbors with Gaussian mixture embedding for few-shot knowledge graph completion
Graph4Web: A relation-aware graph attention network for web service classification
GFCNet: Utilizing graph feature collection networks for coronavirus knowledge graph embeddings
SparseMult: A Tensor Decomposition model based on Sparse Relation Matrix
Application of Bayesian networks to generate synthetic health data
ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding