This is the code for SGIR, a semi-supervised framework for Graph Imbalanced Regression. Data imbalance is easily found in annotated data when the observations of certain continuous label values are ...

The goal of this repository is to provide an overview of knowledge graphs in the domain of biomedicine and of resources for their construction. This is achieved in four complementary ways: A survey ...

Abstract: In recent years, graph convolutional networks (GCNs) have been introduced for hyperspectral image (HSI) classification due to their ability to effectively process the inherent graph ...

Abstract: Neural architecture search (NAS) is crucial for text representation in natural language processing (NLP); however, much less work on NAS for text classification has been proposed compared ...