Simple and Deep Graph Convolutional Networks

Benchmark Model Rank Results
graph-classification-on-peptides-funcGCNII#41AP: 0.5543±0.0078
graph-regression-on-peptides-structGCNII#34MAE: 0.3471±0.0010
link-prediction-on-pcqm-contactGCNII#4Hits@1: 0.1325±0.0009Hits@3: 0.3607±0.0003Hits@10: 0.8116±0.0009
node-classification-on-actorGCNII#17Accuracy: 37.44 ± 1.30
node-classification-on-chameleonGCNII#36Accuracy: 63.86 ± 3.04
node-classification-on-chameleon-60-20-20GCNII*#221:1 Accuracy: 62.8 ± 2.87
node-classification-on-chameleon-60-20-20GCNII#291:1 Accuracy: 60.35 ± 2.7
node-classification-on-citeseer-48-32-20GCNII#51:1 Accuracy: 77.33 ± 1.48
node-classification-on-citeseer-60-20-20GCNII*#51:1 Accuracy: 81.83 ± 1.78
node-classification-on-citeseer-60-20-20GCNII#111:1 Accuracy: 81.58 ± 1.3
node-classification-on-citeseer-fullGCNII*#4Accuracy: 77.13%
node-classification-on-citeseer-with-publicGCNII#15Accuracy: 73.4%
node-classification-on-coco-spGCNII#16macro F1: 0.1404±0.0011
node-classification-on-cora-48-32-20-fixedGCNII#21:1 Accuracy: 88.37 ± 1.25
node-classification-on-cora-60-20-20-randomGCNII#121:1 Accuracy: 88.98 ± 1.33
node-classification-on-cora-60-20-20-randomGCNII*#141:1 Accuracy: 88.93 ± 1.37
node-classification-on-cora-full-supervisedGCNII#1Accuracy: 88.49%
node-classification-on-cora-with-public-splitGCNII#3Accuracy: 85.5%
node-classification-on-cornellGCNII#33Accuracy: 77.86 ± 3.79
node-classification-on-cornell-60-20-20GCNII*#191:1 Accuracy: 90.49 ± 4.45
node-classification-on-cornell-60-20-20GCNII#201:1 Accuracy: 89.18 ± 3.96
node-classification-on-film-60-20-20-randomGCNII*#91:1 Accuracy: 41.54 ± 0.99
node-classification-on-film-60-20-20-randomGCNII#161:1 Accuracy: 40.82 ± 1.79
node-classification-on-geniusGCNII#11Accuracy: 90.24 ± 0.09
node-classification-on-non-homophilicGCNII*#191:1 Accuracy: 90.49 ± 4.45
node-classification-on-non-homophilicGCNII#201:1 Accuracy: 89.18 ± 3.96
node-classification-on-non-homophilic-1GCNII*#191:1 Accuracy: 89.12 ± 3.06
node-classification-on-non-homophilic-1GCNII#211:1 Accuracy: 83.25 ± 2.69
node-classification-on-non-homophilic-10GCNII#71:1 Accuracy: 37.44 ± 1.30
node-classification-on-non-homophilic-11GCNII#221:1 Accuracy: 63.86 ± 3.04
node-classification-on-non-homophilic-12GCNII#251:1 Accuracy: 38.47 ± 1.58
node-classification-on-non-homophilic-13GCNII#91:1 Accuracy: 82.92 ± 0.59
node-classification-on-non-homophilic-14GCNII#131:1 Accuracy: 90.24 ± 0.09
node-classification-on-non-homophilic-15GCNII#181:1 Accuracy: 63.39 ± 0.61
node-classification-on-non-homophilic-2GCNII*#191:1 Accuracy: 88.52 ± 3.02
node-classification-on-non-homophilic-2GCNII#251:1 Accuracy: 82.46 ± 4.58
node-classification-on-non-homophilic-4GCNII*#201:1 Accuracy: 62.8 ± 2.87
node-classification-on-non-homophilic-4GCNII#261:1 Accuracy: 60.35 ± 2.7
node-classification-on-non-homophilic-6GCNII*#161:1 Accuracy: 66.42±0.56
node-classification-on-non-homophilic-6GCNII#181:1 Accuracy: 66.38±0.45
node-classification-on-non-homophilic-7GCNII#211:1 Accuracy: 77.86 ± 3.79
node-classification-on-non-homophilic-8GCNII#201:1 Accuracy: 80.39 ± 3.40
node-classification-on-non-homophilic-9GCNII#211:1 Accuracy: 77.57 ± 3.83
node-classification-on-pascalvoc-sp-1GCNII#19macro F1: 0.1698±0.0080
node-classification-on-penn94GCNII#14Accuracy: 82.92 ± 0.59
node-classification-on-ppiGCNII*#2F1: 99.56
node-classification-on-pubmed-48-32-20-fixedGCNII#11:1 Accuracy: 90.15 ± 0.43
node-classification-on-pubmed-60-20-20-randomGCNII*#171:1 Accuracy: 89.98 ± 0.52
node-classification-on-pubmed-60-20-20-randomGCNII#201:1 Accuracy: 89.8 ± 0.3
node-classification-on-pubmed-full-supervisedGCNII*#4Accuracy: 90.30%
node-classification-on-pubmed-with-publicGCNII#15Accuracy: 80.2%
node-classification-on-squirrelGCNII#36Accuracy: 38.47 ± 1.58
node-classification-on-squirrel-60-20-20GCNII#291:1 Accuracy: 38.81 ± 1.97
node-classification-on-squirrel-60-20-20GCNII*#311:1 Accuracy: 38.31 ± 1.3
node-classification-on-texasGCNII#39Accuracy: 77.57 ± 3.83
node-classification-on-texas-60-20-20-randomGCNII*#201:1 Accuracy: 88.52 ± 3.02
node-classification-on-texas-60-20-20-randomGCNII#271:1 Accuracy: 82.46 ± 4.58
node-classification-on-wisconsinGCNII#38Accuracy: 80.39 ± 3.40
node-classification-on-wisconsin-60-20-20GCNII*#191:1 Accuracy: 89.12 ± 3.06
node-classification-on-wisconsin-60-20-20GCNII#231:1 Accuracy: 83.25 ± 2.69
node-property-prediction-on-ogbn-arxivGCNII#48Test Accuracy: 0.7274 ± 0.0016Ext. data: No