Signed attention based graph neural network for graphs with heterophily

Yang Wu, Liang Hu, Yu Wang

Abstract: Highlights•Signed attention mechanism can capture the complex relationship on graphs.•Exactly higher-order neighborhood aggregation can encode the positional information of neighborhoods.•A novel GNN model based on the above two techniques is proposed.•Achieving a significant improvement over SOTA on graphs with heterophily.