Node Property Prediction on ogbn-papers100M

20개 결과 · ⬇ CSV · JSON

Test Accuracy

Rank	Model	Test Accuracy	Ext. data	Validation Accuracy	Number of params	Paper	Code	Year
1	GLEM+GIANT+GAMLP	0.7037 ± 0.0002	Yes	0.7354 ± 0.0001	154775375	Learning on Large-scale Text-attributed Graphs via Variational Inference	andyjzhao/glem · AndyJZhao/GLEM	2022
2	GIANT-XRT+GAMLP+RLU (use raw text)	0.6967 ± 0.0005	Yes	0.7305 ± 0.0004	21551631	Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction	amzn/pecos · elichienxD/deep_gcns_torch · elichienxD/SAGN_with_SLE · +1	2021
3	GAMLP+RLU+SCR	0.6842 ± 0.0015	No	0.7188 ± 0.0007	67560875	SCR: Training Graph Neural Networks with Consistency Regularization	THUDM/SCR · thudm/scr · thudm/crgnn · +1	2021
4	SAGN+SLE (4 stages)	0.6830 ± 0.0008	No	0.7163 ± 0.0007	8556888	Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training	skepsun/SAGN_with_SLE	2021
5	GAMLP+RLU	0.6825 ± 0.0011	No	0.7159 ± 0.0005	16308751
6	GAMLP+SCR-m	0.6816 ± 0.0012	No	0.7186 ± 0.0008	67560875	SCR: Training Graph Neural Networks with Consistency Regularization	THUDM/SCR · thudm/scr · thudm/crgnn · +1	2021
7	GAMLP+SCR	0.6814 ± 0.0008	No	0.7190 ± 0.0007	67560875	SCR: Training Graph Neural Networks with Consistency Regularization	THUDM/SCR · thudm/scr · thudm/crgnn · +1	2021
8	FSGNN	0.6807 ± 0.0006	No	0.7175 ± 0.0007	16453301	Improving Graph Neural Networks with Simple Architecture Design	sunilkmaurya/FSGNN	2021
9	SAGN+SLE	0.6800 ± 0.0015	No	0.7131 ± 0.0010	8556888	Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training	skepsun/SAGN_with_SLE	2021
10	GAMLP	0.6771 ± 0.0020	No	0.7117 ± 0.0014	16308751
11	TransformerConv	0.6736 ± 0.0010	No	0.7172 ± 0.0005	883378	Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification	PaddlePaddle/PGL · lucidrains/graph-transformer-pytorch · willyfh/graph-transformer	2020
12	shaDow-GAT	0.6708±0.0017	No	0.7073± 0.0011	4205544	Decoupling the Depth and Scope of Graph Neural Networks	facebookresearch/shaDow_GNN	2022
13	GraphSAGE_res_incep	0.6706 ± 0.0017	No	0.7032 ± 0.0011	5755172	Inductive Representation Learning on Large Graphs	pyg-team/pytorch_geometric · dmlc/dgl · dmlc/dgl · +17	2017
14	SAGN	0.6675 ± 0.0084	No	0.7034 ± 0.0099	6098092	Scalable and Adaptive Graph Neural Networks with Self-Label-Enhanced training	skepsun/SAGN_with_SLE	2021
15	SIGN-XL	0.6606 ± 0.0019	No	0.6984 ± 0.0006	7180460	SIGN: Scalable Inception Graph Neural Networks	dmlc/dgl · twitter-research/sign · facebookresearch/NARS · +2	2020
16	PCAPass + LightGBM	0.6591 ± 0.0003	No	0.6982 ± 0.0002	0	Dimensionality Reduction Meets Message Passing for Graph Node Embeddings	ksadowski13/PCAPass	2022
17	SIGN	0.6568 ± 0.0006	No	0.6932 ± 0.0006	1008812	SIGN: Scalable Inception Graph Neural Networks	dmlc/dgl · twitter-research/sign · facebookresearch/NARS · +2	2020
18	SGC	0.6329 ± 0.0019	No	0.6648 ± 0.0020	144044	Simplifying Graph Convolutional Networks	dmlc/dgl · dmlc/dgl · dmlc/dgl · +4	2019
19	Node2vec	0.5560 ± 0.0023	No	0.5807 ± 0.0028	14215818412	node2vec: Scalable Feature Learning for Networks	dmlc/dgl · shenweichen/GraphEmbedding · aditya-grover/node2vec · +17	2016
20	MLP	0.4724 ± 0.0031	No	0.4960 ± 0.0029	144044	Open Graph Benchmark: Datasets for Machine Learning on Graphs	snap-stanford/ogb · snap-stanford/ogb · snap-stanford/ogb · +18	2020