research
∙
11/30/2022
Directed Acyclic Graph Structure Learning from Dynamic Graphs
Estimating the structure of directed acyclic graphs (DAGs) of features (...
share
research
∙
09/28/2022
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
Most Graph Neural Networks (GNNs) predict the labels of unseen graphs by...
research
∙
01/19/2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias
Most existing Graph Neural Networks (GNNs) are proposed without consider...
research
∙
11/20/2021
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
Graph Neural Networks (GNNs) are proposed without considering the agnost...
research
∙
11/30/2020
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Heterogeneous graphs (HGs) also known as heterogeneous information netwo...
research
∙
06/29/2020
