| node-classification-on-yelpchi | GAT+JK | #5 | AUC-ROC: 90.04 |
| fraud-detection-on-yelp-fraud | GAT+JK | #6 | AUC-ROC: 90.04 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-deezer-europe | MLP-2 | #14 | 1:1 Accuracy: 66.55±0.72 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-deezer-europe | GCN+JK | #23 | 1:1 Accuracy: 60.99±0.14 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-deezer-europe | GAT+JK | #25 | 1:1 Accuracy: 59.66±0.92 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-deezer-europe | LINK | #26 | 1:1 Accuracy: 57.71±0.36 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-deezer-europe | LProp (2hop) | #27 | 1:1 Accuracy: 56.96±0.26 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-deezer-europe | L Prop (1hop) | #28 | 1:1 Accuracy: 56.50±0.41 |
| node-classification-on-non-homophilic-heterophilic-graphs-on-wisconsin-60-20-20-random-splits | MLP-2 | #14 | 1:1 Accuracy: 93.87 ± 3.33 |
| node-classification-on-penn94 | GCNJK | #21 | Accuracy: 81.63 ± 0.54 |
| node-classification-on-penn94 | LINK | #25 | Accuracy: 80.79 ± 0.49 |
| node-classification-on-penn94 | GATJK | #26 | Accuracy: 80.69 ± 0.36 |
| node-classification-on-penn94 | L Prop 2-hop | #34 | Accuracy: 74.13 ± 0.46 |
| node-classification-on-penn94 | MLP | #35 | Accuracy: 73.61 ± 0.40 |
| node-classification-on-penn94 | L Prop 1-hop | #37 | Accuracy: 63.21 ± 0.39 |
| node-classification-on-genius | LINK | #26 | Accuracy: 73.56 ± 0.14 |
| node-classification-on-genius | L Prop 2-hop | #27 | Accuracy: 67.04 ± 0.20 |
| node-classification-on-genius | L Prop 1-hop | #28 | Accuracy: 66.02 ± 0.16 |
| node-classification-on-genius | GATJK | #29 | Accuracy: 56.70 ± 2.07 |