paper-with-me

Node Classification 벤치마크

Node Classification on PATTERN

11개 결과 · ⬇ CSV · JSON

Accuracy

86.51 87.05 87.58 88.12 88.66 2020-03 2026-09 GatedGCN — 86.508 (2020-03-02) EGT — 86.821 (2021-08-07) GPS — 86.685 (2022-05-25) Exphormer — 86.74 (2023-03-10) GPTrans-Nano — 86.734 (2023-05-19) GRIT — 87.196 (2023-05-27) EIGENFORMER — 86.738 (2024-01-31) TIGT — 86.68 (2024-02-03) CKGCN — 88.661 (2024-04-21) NeuralWalker — 86.977 (2024-06-05) GatedGCN+ — 87.029 (2025-02-13) GatedGCN — 86.508 (2020-03-02) EGT — 86.821 (2021-08-07) GRIT — 87.196 (2023-05-27) CKGCN — 88.661 (2024-04-21)
RankModel Accuracy PaperCodeYear
1 CKGCN 88.661 CKGConv: General Graph Convolution with Continuous Kernels networkslab/ckgconv 2024
2 GRIT 87.196 Graph Inductive Biases in Transformers without Message Passing liamma/grit · linusbao/MoSE 2023
3 GatedGCN+ 87.029 ± 0.037 Unlocking the Potential of Classic GNNs for Graph-level Tasks: Simple Architectures Meet Excellence LUOyk1999/GNNPlus 2025
4 NeuralWalker 86.977 ± 0.012 Learning Long Range Dependencies on Graphs via Random Walks borgwardtlab/neuralwalker 2024
5 EGT 86.821 Global Self-Attention as a Replacement for Graph Convolution shamim-hussain/egt_pytorch · shamim-hussain/egt · shamim-hussain/egt_triangular 2021
6 Exphormer 86.74 Exphormer: Sparse Transformers for Graphs hamed1375/exphormer 2023
7 EIGENFORMER 86.738 Graph Transformers without Positional Encodings 2024
8 GPTrans-Nano 86.734±0.008 Graph Propagation Transformer for Graph Representation Learning czczup/gptrans 2023
9 GPS 86.685 Recipe for a General, Powerful, Scalable Graph Transformer rampasek/GraphGPS · hamed1375/exphormer · graphcore/ogb-lsc-pcqm4mv2 · +1 2022
10 TIGT 86.680 Topology-Informed Graph Transformer leemingo/tigt · leemingo/cy2mixer 2024
11 GatedGCN 86.508 Benchmarking Graph Neural Networks graphdeeplearning/benchmarking-gnns · PaddlePaddle/PGL · PaddlePaddle/PGL · +12 2020
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