Research map / Graph learning / GNN architectures
Graph Pointer Neural Networks
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use GPNN's selectively ranked non-local aggregation instead of the strongest prior method | Node classification · Chameleon | accuracy: 1.9% | Helped |
| Use GPNN's selectively ranked non-local aggregation instead of the strongest prior method | Node classification · Cornell | accuracy: 3.0% | Helped |
| Use GPNN's selectively ranked non-local aggregation instead of the strongest prior methods | Node classification · six heterophilic graph datasets | accuracy: 6.3% | Helped |
| Jointly optimize node ranking with the classification task using the pointer network rather than Node2Seq attention ranking | GPNN node ranking · six heterophilic graph datasets | homophily ratio: 46% | Helped |
| Use GPNN rather than GCN or GAT as the number of layers grows | Node classification · Chameleon | test accuracy decay: 18%; 33%; 6% | Helped |
Closest papers by meaning
- Pointer Graph Networks (NeurIPS 2020 · similarity 0.90)
- Position-aware Graph Neural Networks (ICML 2019 · similarity 0.90)
- Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs (NeurIPS 2022 · similarity 0.89)
- Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning (ICLR 2025 · similarity 0.88)
- Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness–Generalization Perspective (NeurIPS 2025 · similarity 0.88)
- Integrating Co-Training with Edge Discrimination to Enhance Graph Neural Networks Under Heterophily (AAAI 2025 · similarity 0.88)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.