Graph neural networks (GNNs) are important tools for transductive learning tasks, such as node classification in graphs, due to their expressive power capturing complex interdependency between nodes. To enable graph network learning, existing works typically assume that labeled nodes, from two or multiple classes, provided, so a discriminative classifier can be learned the data. In reality, thi...