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아카이브 평가 54건 · 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
WWL	Accuracy 59.13%	Wasserstein Weisfeiler-Lehman Graph Kernels 2019-06-04	코드 1 · 코드 2
GAT-GC (f-Scaled)	Accuracy 58.45	Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation 2019-07-04	코드 1
δ-2-LWL	Accuracy 58.2%	Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings 2019-04-02	코드 1
GraphSAGE	Accuracy 58.2%	A Fair Comparison of Graph Neural Networks for Graph Classification 2019-12-20	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
DAGCN	Accuracy 58.17%	DAGCN: Dual Attention Graph Convolutional Networks 2019-04-04	코드 1
Evolution of Graph Classifiers	Accuracy 55.67	Evolution of Graph Classifiers 2019-10-04	코드 1
CapsGNN	Accuracy 54.67%	Capsule Graph Neural Network 2019-05-01	코드 1
DGK	Accuracy 53.43%	Deep Graph Kernels 2015-08-10	연결 없음
R-GIN + PANDA	Accuracy 53.1	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1
ECC (5 scores)	Accuracy 52.67%	Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs 2017-04-10	코드 1 · 코드 2
SPI-GCN	Accuracy 50.17%	SPI-GCN: A Simple Permutation-Invariant Graph Convolutional Network 2019-04-08	연결 없음
Fea2Fea-s2	Accuracy 48.5	Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks 2021-06-24	코드 1
VRGC	Accuracy 48.4%	Variational Recurrent Neural Networks for Graph Classification 2019-02-07	코드 1
GIN + PANDA	Accuracy 46.2	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1
NDP	Accuracy 43.9%	Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling 2019-10-24	코드 1
R-GCN + PANDA	Accuracy 43.9	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1
SF + RFC	Accuracy 43.7%	A Simple Baseline Algorithm for Graph Classification 2018-10-22	코드 1 · 코드 2 · 코드 3
Local Topological Profile (LTP)	Accuracy 42.5 ± 4.1 Accuracy (10-fold) 42.5 ± 4.1	Strengthening structural baselines for graph classification using Local Topological Profile 2023-05-01	코드 1
LDP	Accuracy 35.3%	A simple yet effective baseline for non-attributed graph classification 2018-11-08	코드 1 · 코드 2
GCN + PANDA	Accuracy 31.55	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1
DEMO-Net(weight)	Accuracy 27.2	DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification 2019-06-05	코드 1
BC + Capsules	Accuracy 27%	Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations 2019-02-22	연결 없음
1-NMFPool	Accuracy 24.1%	A Non-Negative Factorization approach to node pooling in Graph Convolutional Neural Networks 2019-09-07	연결 없음
G-Tuning	Accuracy (10-fold) 26.70	Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns 2023-12-21	코드 1