Scientific Research Publishing

Kipf, T. and Welling, M. (2016) Semi-Supervised Classification with Graph Convolutional Networks. arXiv: 1609.02907.

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
Scientific Research Publishing

Kipf, T.N. and Welling, M. (2017) Semi-Supervised Classification with Graph Convolutional Networks.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
EurekAlert!

Boundary-aware semi-supervised segmentation boosts 3D medical image accuracy

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
IEEE

Semi-supervised Graph Neural Networks with Incremental Learning for Fraud Detection

Abstract: The fraud detection methods based on graph neural networks (GNN) have better performance in financial transaction scenarios with frequent interaction. However, camouflage is still the most ...
IEEE

Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data

Abstract: Graph-based semi-supervised learning has been shown to be one of the most effective classification approaches, as it can exploit connectivity patterns between labeled and unlabeled samples ...