| Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs | ✓ Link | 86.49 ± 7.35 | Diag-NSD | 2022-02-09 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 86.49 ± 6.73 | ACMII-GCN++ | 2022-10-14 |
| Finding Global Homophily in Graph Neural Networks When Meeting Heterophily | ✓ Link | 85.95 ± 5.10 | GloGNN++ | 2022-05-15 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 85.95 ± 5.64 | ACMII-GCN | 2022-10-14 |
| Deformable Graph Convolutional Networks | ✓ Link | 85.95±4.37 | Deformable GCN | 2021-12-29 |
| Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks | ✓ Link | 85.68 ± 6.63 | GGCN | 2021-02-12 |
| Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs | ✓ Link | 85.68 ± 6.51 | Gen-NSD | 2022-02-09 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 85.68 ± 4.84 | ACM-GCN+ | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 85.68 ± 5.8 | ACM-GCN++ | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 85.41 ± 5.3 | ACMII-GCN+ | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 85.14 ± 6.07 | ACM-GCN | 2022-10-14 |
| Non-Local Graph Neural Networks | ✓ Link | 84.9 ± 5.7 | NLMLP | 2020-05-29 |
| Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs | ✓ Link | 84.86 ± 4.71 | O(d) - NSD | 2022-02-09 |
| Finding Global Homophily in Graph Neural Networks When Meeting Heterophily | ✓ Link | 83.51 ± 4.26 | GloGNN | 2022-05-15 |
| Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs | ✓ Link | 82.70 ± 5.28 | H2GCN | 2020-06-20 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 82.43 ± 5.44 | ACM-SGC-1 | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 82.43 ± 5.44 | ACM-SGC-2 | 2022-10-14 |
| Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns | ✓ Link | 81.62 ±3.90 | WRGAT | 2021-06-11 |
| Addressing Heterophily in Node Classification with Graph Echo State Networks | ✓ Link | 81.14 ± 6.00 | GESN | 2023-05-14 |
| Adaptive Universal Generalized PageRank Graph Neural Network | ✓ Link | 78.11 ± 6.55 | GPRGCN | 2020-06-14 |
| Simple and Deep Graph Convolutional Networks | ✓ Link | 77.86 ± 3.79 | GCNII | 2020-07-04 |
| Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods | ✓ Link | 77.84 ± 5.81 | LINKX | 2021-10-27 |
| Beyond Low-frequency Information in Graph Convolutional Networks | ✓ Link | 76.76 ± 5.87 | FAGCN | 2021-01-04 |
| MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing | ✓ Link | 73.51 ± 6.34 | MixHop | 2019-04-30 |
| Geom-GCN: Geometric Graph Convolutional Networks | ✓ Link | 60.54 ± 3.67 | Geom-GCN | 2020-02-13 |
| Non-Local Graph Neural Networks | ✓ Link | 57.6 ± 5.5 | NLGCN | 2020-05-29 |
| Non-Local Graph Neural Networks | ✓ Link | 54.7 ± 7.6 | NLGAT | 2020-05-29 |