| Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs | ✓ Link | 89.41 ± 4.74 | O(d)-NSD | 2022-02-09 |
| Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs | ✓ Link | 89.21 ± 3.84 | Gen-NSD | 2022-02-09 |
| Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs | ✓ Link | 88.63 ± 2.75 | Diag-NSD | 2022-02-09 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 88.43 ± 3.22 | ACM-GCN | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 88.43 ± 2.39 | ACM-GCN+ | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 88.43 ± 3.66 | ACMII-GCN++ | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 88.24 ± 3.16 | ACM-GCN++ | 2022-10-14 |
| Finding Global Homophily in Graph Neural Networks When Meeting Heterophily | ✓ Link | 88.04 ± 3.22 | GloGNN++ | 2022-05-15 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 88.04 ± 3.66 | ACMII-GCN+ | 2022-10-14 |
| Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs | ✓ Link | 87.65 ± 4.98 | H2GCN | 2020-06-20 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 87.45 ± 3.74 | ACMII-GCN | 2022-10-14 |
| Non-Local Graph Neural Networks | ✓ Link | 87.3 ± 4.3 | NLMLP | 2020-05-29 |
| Finding Global Homophily in Graph Neural Networks When Meeting Heterophily | ✓ Link | 87.06 ± 3.53 | GloGNN | 2022-05-15 |
| Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns | ✓ Link | 86.98 ± 3.78 | WRGAT | 2021-06-11 |
| Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks | ✓ Link | 86.86 ± 3.29 | GGCN | 2021-02-12 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 86.47 ± 3.77 | ACM-SGC-1 | 2022-10-14 |
| Revisiting Heterophily For Graph Neural Networks | ✓ Link | 86.47 ± 3.77 | ACM-SGC-2 | 2022-10-14 |
| Addressing Heterophily in Node Classification with Graph Echo State Networks | ✓ Link | 83.33 ± 3.81 | GESN | 2023-05-14 |
| Adaptive Universal Generalized PageRank Graph Neural Network | ✓ Link | 82.55 ± 6.23 | GPRGCN | 2020-06-14 |
| Simple and Deep Graph Convolutional Networks | ✓ Link | 80.39 ± 3.40 | GCNII | 2020-07-04 |
| Beyond Low-frequency Information in Graph Convolutional Networks | ✓ Link | 79.61 ± 1.58 | FAGCN | 2021-01-04 |
| MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing | ✓ Link | 75.88 ± 4.90 | MixHop | 2019-04-30 |
| Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods | ✓ Link | 75.49 ± 5.72 | LINKX | 2021-10-27 |
| Geom-GCN: Geometric Graph Convolutional Networks | ✓ Link | 64.51 ± 3.66 | Geom-GCN | 2020-02-13 |
| Non-Local Graph Neural Networks | ✓ Link | 60.2 ± 5.3 | NLGCN | 2020-05-29 |
| Non-Local Graph Neural Networks | ✓ Link | 56.9 ± 7.3 | NLGAT | 2020-05-29 |