Node Classification on Reddit

16개 결과 · ⬇ CSV · JSON

Accuracy

Rank	Model	Accuracy	Micro-F1	Paper	Code	Year
1	BNS-GCN	97.17%	–	BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling	gatech-eic/bns-gcn · RICE-EIC/BNS-GCN	2022
2	CoFree-GNN	97.14±0.02%	–	Communication-Free Distributed GNN Training with Vertex Cut		2023
3	shaDow-GAT	97.13%	–	Decoupling the Depth and Scope of Graph Neural Networks	facebookresearch/shaDow_GNN	2022
4	shaDow-SAGE	97.03%	–	Decoupling the Depth and Scope of Graph Neural Networks	facebookresearch/shaDow_GNN	2022
5	JKNet+DropEdge	97.02%	–	DropEdge: Towards Deep Graph Convolutional Networks on Node Classification	GraphSAINT/GraphSAINT · GraphSAINT/GraphSAINT · DropEdge/DropEdge · +4	2019
6	GraphSAINT	97.0%	–	GraphSAINT: Graph Sampling Based Inductive Learning Method	dmlc/dgl · GraphSAINT/GraphSAINT · thudm/graphmae2 · +5	2019
7	EnGCN	96.65%	–	A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking	VITA-Group/Large_Scale_GCN_Benchmarking · vita-group/large_scale_gcn_benchmarking	2022
8	SIGN	96.60%	–	SIGN: Scalable Inception Graph Neural Networks	dmlc/dgl · twitter-research/sign · facebookresearch/NARS · +2	2020
9	ASGCN	96.27%	–	Adaptive Sampling Towards Fast Graph Representation Learning	dmlc/dgl · huangwb/AS-GCN	2018
10	PCAPass + XGBoost	96.26 ± 0.02%	–	Dimensionality Reduction Meets Message Passing for Graph Node Embeddings	ksadowski13/PCAPass	2022
11	SSGC	95.3	–	Simple Spectral Graph Convolution	allenhaozhu/SSGC · hazdzz/SSGC	2021
12	VQ-GNN (SAGE-Mean)	94.5 ± .0024	–	VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization	devnkong/VQ-GNN	2021
13	GraphSAGE	94.32%	–	Inductive Representation Learning on Large Graphs	pyg-team/pytorch_geometric · dmlc/dgl · dmlc/dgl · +17	2017
14	FastGCN	93.70%	–	FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling	matenure/FastGCN · gkunnan97/fastgcn_pytorch · jiechenjiechen/FastGCN-matlab · +1	2018
15	TGCL+ResNet	81.06±1.18%	–	Deeper-GXX: Deepening Arbitrary GNNs		2021
16	GRACE	–	94.2 ± 0.0	Deep Graph Contrastive Representation Learning	dmlc/dgl · CRIPAC-DIG/GRACE · ycremar/DIG-SSL	2020