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cs.LG2021
RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data
Mahsa Ghorbani, Anees Kazi, Mahdieh Soleymani Baghshah +2
Disease prediction is a well-known classification problem in medical applications. GCNs provide a powerful tool for analyzing the patients' features relative to each other. This ca…
cs.LG2018
Adversarial Classifier for Imbalanced Problems
Ehsan Montahaei, Mahsa Ghorbani, Mahdieh Soleymani Baghshah +1
Adversarial approach has been widely used for data generation in the last few years. However, this approach has not been extensively utilized for classifier training. In this paper…
cs.LG2018
MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks
Mahsa Ghorbani, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
Graph embedding is an important approach for graph analysis tasks such as node classification and link prediction. The goal of graph embedding is to find a low dimensional represen…