[PDF][PDF] Adr-gnn: advection-diffusion-reaction graph neural networks
Graph neural networks (GNNs) have shown remarkable success in learning representations
for graph-structured data. However, GNNs still face challenges in modeling complex …
for graph-structured data. However, GNNs still face challenges in modeling complex …
AutoDAW: Automated Data Augmentation for Graphs With Weak Information
M Nie, D Chen, D Wang, H Chen - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Data augmentation has been widely used across various research domains in recent years.
However, data augmentation applied to real-world graph-structured data tends to suffer from …
However, data augmentation applied to real-world graph-structured data tends to suffer from …
AutoMTNAS: Automated meta-reinforcement learning on graph tokenization for graph neural architecture search
M Nie, D Chen, H Chen, D Wang - Knowledge-Based Systems, 2025 - Elsevier
Graph neural networks have achieved breakthroughs in various fields due to their powerful
automated representation capabilities for graph. Designing effective graph neural …
automated representation capabilities for graph. Designing effective graph neural …