| From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited | ✓ Link | 77.5 | OGC | 2023-09-24 |
| Graph Random Neural Network for Semi-Supervised Learning on Graphs | ✓ Link | 75.4 ± 0.4 | GRAND | 2020-05-22 |
| Learning Discrete Structures for Graph Neural Networks | ✓ Link | 75.0% | LDS-GNN | 2019-03-28 |
| The Split Matters: Flat Minima Methods for Improving the Performance of GNNs | ✓ Link | 74.73 ± 0.6% | Graph-MLP + PGN | 2023-06-15 |
| Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework | ✓ Link | 74.6% | CPF-tra-APPNP | 2021-03-04 |
| GraphMix: Improved Training of GNNs for Semi-Supervised Learning | ✓ Link | 74.52 ± 0.59 | GraphMix(GCN) | 2019-09-25 |
| A Flexible Generative Framework for Graph-based Semi-supervised Learning | ✓ Link | 74.5% | G3NN | 2019-05-26 |
| Optimization of Graph Neural Networks with Natural Gradient Descent | ✓ Link | 74.28 ± 0.67% | SSP | 2020-08-21 |
| Graph Entropy Minimization for Semi-supervised Node Classification | ✓ Link | 74.2 | GEM | 2023-05-31 |
| From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited | ✓ Link | 74.2 | GGCM | 2023-09-24 |
| Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks | ✓ Link | 73.86% | Truncated Krylov | 2019-06-05 |
| Simple Spectral Graph Convolution | ✓ Link | 73.6 | SSGC | 2021-01-01 |
| Graph Entropy Minimization for Semi-supervised Node Classification | ✓ Link | 73.53 | OKDEEM | 2023-05-31 |
| Simple and Deep Graph Convolutional Networks | ✓ Link | 73.4% | GCNII | 2020-07-04 |
| Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning | ✓ Link | 73.4 ± 0.7 | SEGCN | 2018-09-26 |
| Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks | ✓ Link | 73.32% | Snowball (tanh) | 2019-06-05 |
| Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks | ✓ Link | 73.3 | DSGCN | 2020-03-26 |
| Towards Deeper Graph Neural Networks | ✓ Link | 73.3 ± 0.6 | DAGNN (Ours) | 2020-07-18 |
| Data Augmentation for Graph Neural Networks | ✓ Link | 73.3 ± 1.1 | GCN+GAugO | 2020-06-11 |
| Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification | ✓ Link | 73.14± 0.67 | GCN | 2024-06-13 |
| GraphAIR: Graph Representation Learning with Neighborhood Aggregation and Interaction | ✓ Link | 72.9% | AIR-GCN | 2019-11-05 |
| Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks | ✓ Link | 72.85% | Snowball (linear) | 2019-06-05 |
| Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification | ✓ Link | 72.8% | H-GCN | 2019-02-13 |
| []() | | 72.70% | IncepGCN+DropEdge | |
| Graph Entropy Minimization for Semi-supervised Node Classification | ✓ Link | 72.63 | EEM | 2023-05-31 |
| How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision | ✓ Link | 72.6% | SuperGAT MX | 2022-04-11 |
| Graph Attention Networks | ✓ Link | 72.5 ± 0.7% | GAT | 2017-10-30 |
| Pre-train and Learn: Preserve Global Information for Graph Neural Networks | ✓ Link | 72% | G-APPNP | 2019-10-27 |
| Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages | ✓ Link | 70.96% | CoLinkDistMLP | 2021-06-16 |
| Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages | ✓ Link | 70.79% | CoLinkDist | 2021-06-16 |
| Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages | ✓ Link | 70.27% | LinkDist | 2021-06-16 |
| Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages | ✓ Link | 70.26% | LinkDistMLP | 2021-06-16 |
| Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering | ✓ Link | 70.1% | ChebyNet | 2016-06-30 |
| Diffusion-Convolutional Neural Networks | ✓ Link | 69.4% | DCNN | 2015-11-06 |
| LanczosNet: Multi-Scale Deep Graph Convolutional Networks | ✓ Link | 68.7 ± 1.0 | AdaLanczosNet | 2019-01-06 |
| Inductive Representation Learning on Large Graphs | ✓ Link | 67.2 | GraphSAGE | 2017-06-07 |
| LanczosNet: Multi-Scale Deep Graph Convolutional Networks | ✓ Link | 66.2 ± 1.9 | LanczosNet | 2019-01-06 |
| Gated Graph Sequence Neural Networks | ✓ Link | 64.6% | GGNN | 2015-11-17 |
| Neural Message Passing for Quantum Chemistry | ✓ Link | 64.0 | MPNN | 2017-04-04 |
| Convolutional Networks on Graphs for Learning Molecular Fingerprints | ✓ Link | 61.5% | GCN-FP | 2015-09-30 |