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MUTAG

아카이브 평가 74건 · 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
PSCN	Accuracy 88.95%	Learning Convolutional Neural Networks for Graphs 2016-05-17	코드 1 · 코드 2
BC + Capsules	Accuracy 88.9%	Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations 2019-02-22	연결 없음
edGNN (max)	Accuracy 88.8%	edGNN: a Simple and Powerful GNN for Directed Labeled Graphs 2019-04-18	코드 1
GIN + PANDA	Accuracy 88.75%	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1
NERO	Accuracy 88.68%	Relation order histograms as a network embedding tool 2021-06-09	코드 1
Path up to length h	Accuracy 88.47%	Graph Kernels Based on Linear Patterns: Theoretical and Experimental Comparisons 2019-03-01	코드 1 · 코드 2
U2GNN (Unsupervised)	Accuracy 88.47%	Universal Graph Transformer Self-Attention Networks 2019-09-26	코드 1
FGW wl h=4 sp	Accuracy 88.42%	Optimal Transport for structured data with application on graphs 2018-05-23	코드 1 · 코드 2
SF + RFC	Accuracy 88.4%	A Simple Baseline Algorithm for Graph Classification 2018-10-22	코드 1 · 코드 2 · 코드 3
ECC (5 scores)	Accuracy 88.33%	Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs 2017-04-10	코드 1 · 코드 2
WEGL	Accuracy 88.3%	Wasserstein Embedding for Graph Learning 2020-06-16	코드 1
R-GIN + PANDA	Accuracy 88.2%	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1
AWE	Accuracy 87.87%	Anonymous Walk Embeddings 2018-05-30	코드 1 · 코드 2
Graphlet Kernel	Accuracy 87.7%	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks 2018-10-04	코드 1
CT-Layer	Accuracy 87.58%	DiffWire: Inductive Graph Rewiring via the Lovász Bound 2022-06-15	코드 1 · 코드 2
WKPI-kcenters	Accuracy 87.5%	Learning metrics for persistence-based summaries and applications for graph classification 2019-04-27	코드 1
DGK	Accuracy 87.44%	Deep Graph Kernels 2015-08-10	연결 없음
WWL	Accuracy 87.27%	Wasserstein Weisfeiler-Lehman Graph Kernels 2019-06-04	코드 1 · 코드 2
DAGCN	Accuracy 87.22%	DAGCN: Dual Attention Graph Convolutional Networks 2019-04-04	코드 1
GDL-g (SP)	Accuracy 87.09%	Online Graph Dictionary Learning 2021-02-12	코드 1
edGNN (avg)	Accuracy 86.9%	edGNN: a Simple and Powerful GNN for Directed Labeled Graphs 2019-04-18	코드 1
GAP-Layer (Rcut)	Accuracy 86.9%	DiffWire: Inductive Graph Rewiring via the Lovász Bound 2022-06-15	코드 1 · 코드 2
GAP-Layer (Ncut)	Accuracy 86.9%	DiffWire: Inductive Graph Rewiring via the Lovász Bound 2022-06-15	코드 1 · 코드 2
CapsGNN	Accuracy 86.67%	Capsule Graph Neural Network 2019-05-01	코드 1
FGW wl h=2 sp	Accuracy 86.42%	Optimal Transport for structured data with application on graphs 2018-05-23	코드 1 · 코드 2
ApproxRepSet	Accuracy 86.33%	Rep the Set: Neural Networks for Learning Set Representations 2019-04-03	코드 1
VRGC	Accuracy 86.3%	Variational Recurrent Neural Networks for Graph Classification 2019-02-07	코드 1
k-GNN	Accuracy 86.1%	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks 2018-10-04	코드 1
DGCNN	Accuracy 85.83%	An End-to-End Deep Learning Architecture for Graph Classification 2018-04-29	코드 1 · 코드 2
GCN + PANDA	Accuracy 85.75%	PANDA: Expanded Width-Aware Message Passing Beyond Rewiring 2024-06-06	코드 1