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아카이브 평가 71건 · 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
ACMII-Snowball-2	Accuracy 82.07 ± 1.04	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
ACM-GCN	Accuracy 81.68 ± 0.97	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
ACM-Snowball-2	Accuracy 81.58 ± 1.23	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
ACMII-Snowball-3	Accuracy 81.56 ± 1.15	Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? 2021-09-12	연결 없음
SSP	Accuracy 80.52 ± 0.14	Optimization of Graph Neural Networks with Natural Gradient Descent 2020-08-21	코드 1
NodeNet	Accuracy 80.09%	NodeNet: A Graph Regularised Neural Network for Node Classification 2020-06-16	연결 없음
SplineCNN	Accuracy 79.20%	SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels 2017-11-24	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
GCN-LPA	Accuracy 78.7 ± 0.6	Unifying Graph Convolutional Neural Networks and Label Propagation 2020-02-17	코드 1 · 코드 2
Graph-MLP + SWA	Accuracy 77.99 ± 1.57%	The Split Matters: Flat Minima Methods for Improving the Performance of GNNs 2023-06-15	코드 1
CNMPGNN	Accuracy 76.81±1.40	CN-Motifs Perceptive Graph Neural Networks 2021-11-15	연결 없음
CGT	Accuracy 76.59±0.98	Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community Structures 2023-12-28	코드 1
3ference	Accuracy 76.33	Inferring from References with Differences for Semi-Supervised Node Classification on Graphs 2022-04-11	코드 1
MMA	Accuracy 76.30%	Multi-Mask Aggregators for Graph Neural Networks 2022-11-24	코드 1
AdaGCN	Accuracy 76.22 ± 0.20	AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models 2019-08-14	코드 1
UGT	Accuracy 76.08±2.5	Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity 2023-08-18	코드 1 · 코드 2 · 코드 3
PPNP	Accuracy 75.83% Validation YES	Predict then Propagate: Graph Neural Networks meet Personalized PageRank 2018-10-14	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
CoLinkDist	Accuracy 75.79%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
CoLinkDistMLP	Accuracy 75.77%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
APPNP	Accuracy 75.73%	Predict then Propagate: Graph Neural Networks meet Personalized PageRank 2018-10-14	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
Cleora	Accuracy 75.7	Cleora: A Simple, Strong and Scalable Graph Embedding Scheme 2021-02-03	코드 1 · 코드 2
PairE	Accuracy 75.53	Graph Representation Learning Beyond Node and Homophily 2022-03-03	코드 1
LinkDistMLP	Accuracy 75.25%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
LDS-GNN	Accuracy 75.0	Learning Discrete Structures for Graph Neural Networks 2019-03-28	코드 1 · 코드 2
LinkDist	Accuracy 74.72%	Distilling Self-Knowledge From Contrastive Links to Classify Graph Nodes Without Passing Messages 2021-06-16	코드 1 · 코드 2
DFNet-ATT	Accuracy 74.7 ± 0.4	DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters 2019-10-24	코드 1
G3NN	Accuracy 74.5% Training Split 20 per node with early stopping set Validation YES	A Flexible Generative Framework for Graph-based Semi-supervised Learning 2019-05-26	코드 1
DNAConv	Accuracy 74.50%	Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks 2019-04-09	코드 1
TREE-G	Accuracy 74.5	TREE-G: Decision Trees Contesting Graph Neural Networks 2022-07-06	코드 1
GResNet(LoopyNet)	Accuracy 73.7%	GResNet: Graph Residual Network for Reviving Deep GNNs from Suspended Animation 2019-09-12	코드 1 · 코드 2
GraphVAT	Accuracy 73.7%	Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure 2019-02-20	코드 1