research
∙
09/09/2023
Finding Influencers in Complex Networks: An Effective Deep Reinforcement Learning Approach
Maximizing influences in complex networks is a practically important but...
share
research
∙
08/16/2023
The Expressive Power of Graph Neural Networks: A Survey
Graph neural networks (GNNs) are effective machine learning models for m...
research
∙
07/08/2023
Inductive Meta-path Learning for Schema-complex Heterogeneous Information Networks
Heterogeneous Information Networks (HINs) are information networks with ...
research
∙
12/15/2020
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
Large knowledge graphs often grow to store temporal facts that model the...
research
∙
10/07/2020
Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer
Predicting missing facts in a knowledge graph (KG) is a crucial task in ...
research
∙
05/31/2019
Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
Graph neural networks (GNNs) are shown to be successful in modeling appl...
research
∙
05/24/2019