Papers with Code · CC BY-SA 4.0

Pubmed

아카이브 평가 70건 · 마지막 적재/변경 2026-10-30

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
NCGCN	Accuracy 91.64 ± 0.53	Clarify Confused Nodes via Separated Learning 2023-06-04	코드 1
NCSAGE	Accuracy 91.55 ± 0.38	Clarify Confused Nodes via Separated Learning 2023-06-04	코드 1
ACMII-Snowball-3	Accuracy 91.31 ± 0.6	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
ACM-GCN	Accuracy 90.74 ± 0.5	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
Graph-MLP + SAF	Accuracy 90.64 ± 0.46%	The Split Matters: Flat Minima Methods for Improving the Performance of GNNs 2023-06-15	코드 1
ACMII-Snowball-2	Accuracy 90.56 ± 0.39	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
NodeNet	Accuracy 90.21%	NodeNet: A Graph Regularised Neural Network for Node Classification 2020-06-16	연결 없음
CNMPGNN	Accuracy 90.07± 0.43	CN-Motifs Perceptive Graph Neural Networks 2021-11-15	연결 없음
CoLinkDist	Accuracy 89.58%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
CoLinkDistMLP	Accuracy 89.53%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
SSP	Accuracy 89.36 ± 0.57	Optimization of Graph Neural Networks with Natural Gradient Descent 2020-08-21	코드 1
3ference	Accuracy 88.90	Inferring from References with Differences for Semi-Supervised Node Classification on Graphs 2022-04-11	코드 1
SplineCNN	Accuracy 88.88%	SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels 2017-11-24	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
LinkDist	Accuracy 88.86%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
LinkDistMLP	Accuracy 88.79%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
GCN + Mixup	Accuracy 87.9%	Mixup for Node and Graph Classification 2021-06-01	코드 1
GCN-LPA	Accuracy 87.8 ± 0.6	Unifying Graph Convolutional Neural Networks and Label Propagation 2020-02-17	코드 1 · 코드 2
CGT	Accuracy 86.86±0.12	Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures 2023-12-28	코드 1
GRACE	Accuracy 86.7 ± 0.1	Deep Graph Contrastive Representation Learning 2020-06-07	코드 1 · 코드 2 · 코드 3
CT-Layer (PE)	Accuracy 86.07	DiffWire: Inductive Graph Rewiring via the Lovász Bound 2022-06-15	코드 1 · 코드 2
GNN RH-U	Accuracy 86%	Certifiable Robustness and Robust Training for Graph Convolutional Networks 2019-06-28	코드 1
MMA	Accuracy 86.00%	Multi-Mask Aggregators for Graph Neural Networks 2022-11-24	코드 1
DFNet-ATT	Accuracy 85.2 ± 0.3	DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters 2019-10-24	코드 1
GResNet(LoopyNet)	Accuracy 83.0%	GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation 2019-09-12	코드 1 · 코드 2
PA-GNN	Accuracy 82.92 ± 0.13	Transferring Robustness for Graph Neural Network Against Poisoning Attacks 2019-08-20	코드 1
GResNet(GAT)	Accuracy 82.2%	GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation 2019-09-12	코드 1 · 코드 2
TGCL+ResNet	Accuracy 81.92±0.13	Deeper-GXX: Deepening Arbitrary GNNs 2021-10-26	연결 없음
DSGCN	Accuracy 81.9% Training Split fixed 20 per class	연결 없음 논문 날짜 미기재	연결 없음
GResNet(GCN)	Accuracy 81.7%	GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation 2019-09-12	코드 1 · 코드 2
LoopyNet	Accuracy 81.2%	GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation 2019-09-12	코드 1 · 코드 2