• Link Prediction on High-Dimensional Multiplex Graphs.[Link]
• Transfer Learning with Diffusion Model for Polymer Property Prediction.[Link]
• Attention-based Graph Estimation and Directed Convolution for Prediction of Traffic Conditions.[Link]
• Pre-training with Graph Transformers.[Link]
• Layer-wise self-supervised learning on graphs.[Link]
• GRASP: Accelerating Shortest Path Attacks via Graph Attention.[Link]
• Neural Priority Queues for Graph Neural Networks (GNNs).[Link]
• OCTAL: Graph Representation Learning for LTL Model Checking.[Link]
• Neural Graphical Models.[Link]
• GraphBoost: Adaptive Boosting Node Generation for Class-Imbalanced Graphs.[Link]
• Customizing GNN Architecture for CAD Assembly Recommendation.[Link]