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IMDb-M

아카이브 평가 36건 · 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
U2GNN (Unsupervised)	Accuracy 89.2%	Universal Graph Transformer Self-Attention Networks 2019-09-26	코드 1
TFGW ADJ (L=2)	Accuracy 56.8%	Template based Graph Neural Network with Optimal Transport Distances 2022-05-31	코드 1
TREE-G	Accuracy 56.4%	TREE-G: Decision Trees Contesting Graph Neural Networks 2022-07-06	코드 1
MEWISPool	Accuracy 56.23%	Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks 2021-07-03	코드 1
DUGNN	Accuracy 56.10%	Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning 2019-09-22	코드 1
G_ResNet	Accuracy 54.53%	When Work Matters: Transforming Classical Network Structures to Graph CNN 2018-07-07	연결 없음
sGIN	Accuracy 54.52%	Mutual Information Maximization in Graph Neural Networks 2019-05-21	코드 1 · 코드 2
GIUNet	Accuracy 54%	Graph isomorphism UNet 2023-08-23	코드 1
U2GNN	Accuracy 53.60%	Universal Graph Transformer Self-Attention Networks 2019-09-26	코드 1
SEG-BERT	Accuracy 53.4%	Segmented Graph-Bert for Graph Instance Modeling 2020-02-09	코드 1
GIN-0	Accuracy 52.3%	How Powerful are Graph Neural Networks? 2018-10-01	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15 · 코드 16 · 코드 17 · 코드 18 · 코드 19
WEGL	Accuracy 52%	Wasserstein Embedding for Graph Learning 2020-06-16	코드 1
GFN	Accuracy 51.80%	Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification 2019-05-11	코드 1
1-WL Kernel	Accuracy 51.5%	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks 2018-10-04	코드 1
DropGIN	Accuracy 51.4%	DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks 2021-11-11	코드 1
GFN-light	Accuracy 51.20%	Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification 2019-05-11	코드 1
UGraphEmb-F	Accuracy 50.97%	Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity 2019-04-01	코드 1
Graph-JEPA	Accuracy 50.69%	Graph-level Representation Learning with Joint-Embedding Predictive Architectures 2023-09-27	코드 1
GMT	Accuracy 50.66%	Accurate Learning of Graph Representations with Graph Multiset Pooling 2021-02-23	코드 1
GDL	Accuracy 50.64%	Online Graph Dictionary Learning 2021-02-12	코드 1
δ-2-LWL	Accuracy 50.5%	Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings 2019-04-02	코드 1
CapsGNN	Accuracy 50.27%	Capsule Graph Neural Network 2019-05-01	코드 1
UGraphEmb	Accuracy 50.06%	Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity 2019-04-01	코드 1
Local Topological Profile (LTP)	Accuracy 50.0 ± 4.6 Accuracy (10-fold) 50.0 ± 4.6	Strengthening structural baselines for graph classification using Local Topological Profile 2023-05-01	코드 1
PPGN	Accuracy 50%	Provably Powerful Graph Networks 2019-05-27	코드 1 · 코드 2
InfoGraph	Accuracy 49.69%	InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization 2019-07-31	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5
k-GNN	Accuracy 49.5%	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks 2018-10-04	코드 1
WKPI-kcenters	Accuracy 49.5%	Learning metrics for persistence-based summaries and applications for graph classification 2019-04-27	코드 1
hGANet	Accuracy 49.06%	Graph Representation Learning via Hard and Channel-Wise Attention Networks 2019-07-05	코드 1
ApproxRepSet	Accuracy 48.92%	Rep the Set: Neural Networks for Learning Set Representations 2019-04-03	코드 1