Exploring Geometric GNNs for Scientific Applications
| Type | review |
|---|---|
| Area | AI |
| Published(YearMonth) | 2403 |
| Source | https://arxiv.org/abs/2403.00485 |
| Tag | newsletter |
| Checkbox | |
| Date(of entry) |
Geometric Graph Neural Networks: A Comprehensive Survey
This survey reviews the field of Geometric Graph Neural Networks (GNNs), focusing on their data structures, models, and applications. Geometric GNNs address the unique challenges of processing geometric graphs, which exhibit physical symmetries. The survey unifies existing models from a geometric message passing perspective, summarizes relevant applications and datasets, and discusses future research directions. These networks are crucial for modeling scientific problems involving geometric features.