Classification on CIFAR10 100k

Metric: Accuracy (%) (higher is better)

LeaderboardDataset

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#	Model↕	Accuracy (%)▼	Augmentations	Paper	Date↕	Code
1	GRIT	76.468	No	Graph Inductive Biases in Transformers without M...	2023-05-27	Code
2	TIGT	73.955	No	Topology-Informed Graph Transformer	2024-02-03	Code
3	ARGNP	73.9	No	Automatic Relation-aware Graph Network Prolifera...	2022-05-31	Code
4	DGN	72.84	No	Directional Graph Networks	2020-10-06	Code
5	GPS	72.298	No	Recipe for a General, Powerful, Scalable Graph T...	2022-05-25	Code
6	PNA	70.47	No	Principal Neighbourhood Aggregation for Graph Nets	2020-04-12	Code
7	EIGENFORMER	70.194	No	Graph Transformers without Positional Encodings	2024-01-31	-
8	GatedGCN	69.37	No	Residual Gated Graph ConvNets	2017-11-20	Code
9	EGT	68.702	No	Global Self-Attention as a Replacement for Graph...	2021-08-07	Code
10	GatedGCN	67.312	No	Benchmarking Graph Neural Networks	2020-03-02	Code
11	GraphSage	66.08	No	Inductive Representation Learning on Large Graphs	2017-06-07	Code
12	GAT	65.48	No	Graph Attention Networks	2017-10-30	Code
13	MoNet	53.42	No	Geometric deep learning on graphs and manifolds ...	2016-11-25	Code
14	GIN	53.28	No	How Powerful are Graph Neural Networks?	2018-10-01	Code

#1GRITSOTA
76.468
Accuracy (%)· 2023-05-27
Graph Inductive Biases in Transformers without Message Passing Code
#2TIGT
73.955
Accuracy (%)· 2024-02-03
Topology-Informed Graph Transformer Code
#3ARGNPSOTA
73.9
Accuracy (%)· 2022-05-31
Automatic Relation-aware Graph Network Proliferation Code
#4DGNSOTA
72.84
Accuracy (%)· 2020-10-06
Directional Graph Networks Code
#5GPS
72.298
Accuracy (%)· 2022-05-25
Recipe for a General, Powerful, Scalable Graph Transformer Code
#6PNASOTA
70.47
Accuracy (%)· 2020-04-12
Principal Neighbourhood Aggregation for Graph Nets Code
#7EIGENFORMER
70.194
Accuracy (%)· 2024-01-31
Graph Transformers without Positional Encodings
#8GatedGCNSOTA
69.37
Accuracy (%)· 2017-11-20
Residual Gated Graph ConvNets Code
#9EGT
68.702
Accuracy (%)· 2021-08-07
Global Self-Attention as a Replacement for Graph Convolution Code
#10GatedGCN
67.312
Accuracy (%)· 2020-03-02
Benchmarking Graph Neural Networks Code
#11GraphSageSOTA
66.08
Accuracy (%)· 2017-06-07
Inductive Representation Learning on Large Graphs Code
#12GAT
65.48
Accuracy (%)· 2017-10-30
Graph Attention Networks Code
#13MoNetSOTA
53.42
Accuracy (%)· 2016-11-25
Geometric deep learning on graphs and manifolds using mixture model CNNs Code
#14GIN
53.28
Accuracy (%)· 2018-10-01
How Powerful are Graph Neural Networks?Code