Graph Anomaly Detection with Bi-level Optimization
Graph anomaly detection (GAD) has various applications in finance, healthcare, and
security. Graph Neural Networks (GNNs) are now the primary method for GAD, treating it as …
security. Graph Neural Networks (GNNs) are now the primary method for GAD, treating it as …
Deep hyperbolic convolutional model for knowledge graph embedding
M Lu, Y Li, J Zhang, H Ren, X Zhang - Knowledge-Based Systems, 2024 - Elsevier
Recent advancements in knowledge graph embedding have enabled the representation of
entities and relations in continuous vector spaces. Performing link prediction on incomplete …
entities and relations in continuous vector spaces. Performing link prediction on incomplete …
Hyperbolic Hypergraph Neural Networks for Multi-Relational Knowledge Hypergraph Representation
Knowledge hypergraphs generalize knowledge graphs using hyperedges to connect
multiple entities and depict complicated relations. Existing methods either transform …
multiple entities and depict complicated relations. Existing methods either transform …
Fully Hyperbolic Representation Learning on Knowledge Hypergraph
Knowledge hypergraphs generalize knowledge graphs in terms of utilizing hyperedges to
connect multiple entities and represent complicated relations within them. Existing methods …
connect multiple entities and represent complicated relations within them. Existing methods …