Detecting fraud in multi-relational graphs is a significant difficulty due to the complex nature of fraudulent activities and the inadequacies of conventional Graph Neural Networks (GNNs) in managing ...

Methods: In order to overcome this limitation, based on the existing research on GPM with the lung cancer knowledge graph, this paper introduces the Monte Carlo method and proposes an edge-level multi ...

This is an official release of the paper "Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition", IJCAI-ECAI 2022 [Paper] [Project] The main novelty of the ...

Graph attention, used in GAT and GaAN, assigns weights to nodes based on their importance. ENADPool is a cluster-based hierarchical pooling method that assigns nodes to unique clusters, calculates ...

Graph convolutional networks have been used in machine-learning-based models for power grid applications like voltage estimation for their ability to capture the network topology of the grid. This ...