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Models/GRIT

GRIT

Reported on 10 benchmarks across 4 tasks · 1 paper · 5 SOTA

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

Graphs8 results

Graph RegressiononZINC-full
Test MAE· 2023-05-27
0.023
best: 0.014 (TIGT)
SOTA
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Graph ClassificationonCIFAR10 100k
Accuracy (%)· 2023-05-27
76.468
SOTA
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Node ClassificationonPATTERN
Accuracy· 2023-05-27
87.196
best: 88.661 (CKGCN)
SOTA
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Node ClassificationonCLUSTER
Accuracy· 2023-05-27
80.026
SOTA
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Graph RegressiononZINC
MAE· 2023-05-27
0.059
best: 0.051 (ESA + rings + NodeRWSE + EdgeRWSE)
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Graph RegressiononPCQM4Mv2-LSC
Validation MAE· 2023-05-27
0.0859
best: 0.0235 (ESA (Edge set attention, no positional encodings))
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Graph RegressiononZINC-500k
MAE· 2023-05-27
0.059
best: 0.051 (ESA + rings + NodeRWSE + EdgeRWSE)
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
Graph ClassificationonMNIST
Accuracy· 2023-05-27
98.108
best: 98.423 (CKGCN)
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589

Methodology2 results

ClassificationonCIFAR10 100k
Accuracy (%)· 2023-05-27
76.468
SOTA
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589
ClassificationonMNIST
Accuracy· 2023-05-27
98.108
best: 98.423 (CKGCN)
Graph Inductive Biases in Transformers without Message Passing arXiv:2305.17589