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Models/FIT-GNN

FIT-GNN

Reported on 27 benchmarks across 4 tasks · 1 paper · 25 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Graphs23 results

Graph RegressiononQM9: UATOM
MAE· 2024-10-19
0.63
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph RegressiononZINC 10k
Inference Time (ms)· 2024-10-19
0.00184
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph RegressiononZINC 10k
MAE· 2024-10-19
0.578
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph RegressiononQM9
Inference Time (ms)· 2024-10-19
0.0018
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph RegressiononQM9: ZPVE
MAE· 2024-10-19
0.818
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph RegressiononQM9: del e
MAE· 2024-10-19
0.875
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph RegressiononQM9: mu
MAE· 2024-10-19
0.841
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph ClassificationonAIDS
Accuracy· 2024-10-19
84.3
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph ClassificationonAIDS
Inference Time (ms)· 2024-10-19
0.00155
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph ClassificationonPROTEINS
Inference Time (ms)· 2024-10-19
0.0016
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonDBLP
Inference Time (ms)· 2024-10-19
0.0018
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonPubMed: 5 nodes per class
Accuracy· 2024-10-19
67.6
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonCoauthor CS
Inference Time (ms)· 2024-10-19
0.0017
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonCiteSeer: 5 nodes per class
Accuracy· 2024-10-19
62.4
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonDBLP: 5 nodes per class
Accuracy· 2024-10-19
68.3
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonDBLP: 20 nodes per class
Accuracy· 2024-10-19
0.789
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonCiteseer
Inference Time (ms)· 2024-10-19
0.0018
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonCora
Inference Time (ms)· 2024-10-19
0.0019
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node Classificationonogbn-products
Inference Time (ms)· 2024-10-19
0.0016
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node Classificationonogbn-products: 20 nodes per class
Accuracy· 2024-10-19
0.406
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonPubmed
Inference Time (ms)· 2024-10-19
0.0018
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Node ClassificationonCora: 5 nodes per class
Accuracy· 2024-10-19
72.9
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
Graph ClassificationonPROTEINS
Accuracy· 2024-10-19
82.1
best: 84.91 (HGP-SL)
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001

Methodology4 results

ClassificationonAIDS
Accuracy· 2024-10-19
84.3
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
ClassificationonAIDS
Inference Time (ms)· 2024-10-19
0.00155
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
ClassificationonPROTEINS
Inference Time (ms)· 2024-10-19
0.0016
SOTA
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001
ClassificationonPROTEINS
Accuracy· 2024-10-19
82.1
best: 84.91 (HGP-SL)
FIT-GNN: Faster Inference Time for GNNs Using Coarsening arXiv:2410.15001