Graph Regression on PCQM4Mv2-LSC

Metric: Validation MAE (lower is better)

LeaderboardDataset

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Results

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#	Model↕	Validation MAE▲	Extra Data	Paper	Date↕	Code
1	ESA (Edge set attention, no positional encodings)	0.0235	No	An end-to-end attention-based approach for learn...	2024-02-16	Code
2	EGT + Triangular Attention	0.0671	No	Global Self-Attention as a Replacement for Graph...	2021-08-07	Code
3	TGT-At	0.0671	No	Triplet Interaction Improves Graph Transformers:...	2024-02-07	Code
4	Uni-Mol+	0.0693	No	Highly Accurate Quantum Chemical Property Predic...	2023-03-16	Code
5	Transformer-M	0.0772	No	One Transformer Can Understand Both 2D & 3D Mole...	2022-10-04	Code
6	GPTrans-L	0.0809	No	Graph Propagation Transformer for Graph Represen...	2023-05-19	Code
7	TIGT	0.0826	No	Topology-Informed Graph Transformer	2024-02-03	Code
8	GPTrans-T	0.0833	No	Graph Propagation Transformer for Graph Represen...	2023-05-19	Code
9	GPS	0.0852	No	Recipe for a General, Powerful, Scalable Graph T...	2022-05-25	Code
10	EGT	0.0857	No	Global Self-Attention as a Replacement for Graph...	2021-08-07	Code
11	GRIT	0.0859	No	Graph Inductive Biases in Transformers without M...	2023-05-27	Code
12	Graphormer + GFSA	0.086	No	Graph Convolutions Enrich the Self-Attention in ...	2023-12-07	Code
13	Graphormer	0.0864	No	Do Transformers Really Perform Bad for Graph Rep...	2021-06-09	Code
14	EGT+SSA+Self-ensemble	0.0865	No	The Information Pathways Hypothesis: Transformer...	2023-06-02	Code
15	GRPE-Large	0.0867	No	GRPE: Relative Positional Encoding for Graph Tra...	2022-01-30	Code
16	EGT+SSA	0.0876	No	The Information Pathways Hypothesis: Transformer...	2023-06-02	Code
17	TokenGT	0.091	No	Pure Transformers are Powerful Graph Learners	2022-07-06	Code
18	GIN	0.1195	No	How Powerful are Graph Neural Networks?	2018-10-01	Code
19	GCN	0.1379	No	Semi-Supervised Classification with Graph Convol...	2016-09-09	Code
20	MLP-Fingerprint	0.1753	No	OGB-LSC: A Large-Scale Challenge for Machine Lea...	2021-03-17	Code

#1ESA (Edge set attention, no positional encodings)SOTA
0.0235
Validation MAE· 2024-02-16
An end-to-end attention-based approach for learning on graphs Code
#2EGT + Triangular AttentionSOTA
0.0671
Validation MAE· 2021-08-07
Global Self-Attention as a Replacement for Graph Convolution Code
#3TGT-At
0.0671
Validation MAE· 2024-02-07
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers Code
#4Uni-Mol+
0.0693
Validation MAE· 2023-03-16
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+Code
#5Transformer-M
0.0772
Validation MAE· 2022-10-04
One Transformer Can Understand Both 2D & 3D Molecular Data Code
#6GPTrans-L
0.0809
Validation MAE· 2023-05-19
Graph Propagation Transformer for Graph Representation Learning Code
#7TIGT
0.0826
Validation MAE· 2024-02-03
Topology-Informed Graph Transformer Code
#8GPTrans-T
0.0833
Validation MAE· 2023-05-19
Graph Propagation Transformer for Graph Representation Learning Code
#9GPS
0.0852
Validation MAE· 2022-05-25
Recipe for a General, Powerful, Scalable Graph Transformer Code
#10EGTSOTA
0.0857
Validation MAE· 2021-08-07
Global Self-Attention as a Replacement for Graph Convolution Code
#11GRIT
0.0859
Validation MAE· 2023-05-27
Graph Inductive Biases in Transformers without Message Passing Code
#12Graphormer + GFSA
0.086
Validation MAE· 2023-12-07
Graph Convolutions Enrich the Self-Attention in Transformers!Code
#13GraphormerSOTA
0.0864
Validation MAE· 2021-06-09
Do Transformers Really Perform Bad for Graph Representation?Code
#14EGT+SSA+Self-ensemble
0.0865
Validation MAE· 2023-06-02
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles Code
#15GRPE-Large
0.0867
Validation MAE· 2022-01-30
GRPE: Relative Positional Encoding for Graph Transformer Code
#16EGT+SSA
0.0876
Validation MAE· 2023-06-02
The Information Pathways Hypothesis: Transformers are Dynamic Self-Ensembles Code
#17TokenGT
0.091
Validation MAE· 2022-07-06
Pure Transformers are Powerful Graph Learners Code
#18GINSOTA
0.1195
Validation MAE· 2018-10-01
How Powerful are Graph Neural Networks?Code
#19GCNSOTA
0.1379
Validation MAE· 2016-09-09
Semi-Supervised Classification with Graph Convolutional Networks Code
#20MLP-Fingerprint
0.1753
Validation MAE· 2021-03-17
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs Code