- 1. Improving Graph Neural Networks with Simple Architecture Design
- 2. Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding
- 3. Hierarchical Graph Representation Learning with Differentiable Pooling
- 4. On Explainability of Graph Neural Networks via Subgraph Explorations
- 5. MetaDT: Meta Decision Tree for Interpretable Few-Shot Learning
- 6. Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
- 7. Chest Radiograph Disentanglement for COVID-19 Outcome Prediction
- 8. Context Matters: Graph-based Self-supervised Representation Learning for Medical Images
- 9. Airway Anomaly Detection by Graph Neural Network
- 10. 2D histology meets 3D topology: Cytoarchitectonic brain mapping with Graph Neural Networks
- 11. GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs
- 12. IGCN: Image-to-graph Convolutional Network for 2D/3D Deformable Registration
- 13. Neural Trees for Learning on Graphs
- 14. RelTR: Relation Transformer for Scene Graph Generation
- 15. Decoupling Object Detection from Human-Object Interaction Recognition*
- 16. Spatial-Temporal Transformer for Dynamic Scene Graph Generation
- 17. Target Adaptive Context Aggregation for Video Scene Graph Generation
- 18. Exploiting Long-Term Dependencies for Generating Dynamic Scene Graphs
- 19. Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding
- 20. Learning and Reasoning with the Graph Structure Representation in Robotic Surgery
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