Node Classification On Citeseer Full
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| adaptive-sampling-towards-fast-graph | 79.66% |
| inductive-representation-learning-on-large | 71.40% |
| simple-and-deep-graph-convolutional-networks-1 | 77.13% |
| the-truly-deep-graph-convolutional-networks | 80.50% |
| beyond-homophily-with-graph-echo-state-1 | 74.5±2.1 |
| fdgatii-fast-dynamic-graph-attention-with | 75.6434% |
| fastgcn-fast-learning-with-graph | 77.60% |