Papers with Code · CC BY-SA 4.0

PROTEINS

아카이브 평가 103건 · 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
HGP-SL	Accuracy 84.91	Hierarchical Graph Pooling with Structure Learning 2019-11-14	코드 1 · 코드 2 · 코드 3
rLap (unsupervised)	Accuracy 84.3	Randomized Schur Complement Views for Graph Contrastive Learning 2023-06-06	코드 1
TFGW ADJ (L=2)	Accuracy 82.9	Template based Graph Neural Network with Optimal Transport Distances 2022-05-31	코드 1
ESA (Edge set attention, no positional encodings)	Accuracy 82.679±0.799	An end-to-end attention-based approach for learning on graphs 2024-02-16	코드 1
FIT-GNN	Accuracy 82.1 Inference Time (ms) 0.0016	FIT-GNN: Faster Inference Time for GNNs Using Coarsening 2024-10-19	코드 1
DUGNN	Accuracy 81.70%	Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning 2019-09-22	코드 1
MEWISPool	Accuracy 80.71%	Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks 2021-07-03	코드 1
CIN++	Accuracy 80.5	CIN++: Enhancing Topological Message Passing 2023-06-06	코드 1
SAEPool	Accuracy 80.36%	Relational Reasoning Over Spatial-Temporal Graphs for Video Summarization 2022-04-06	연결 없음
MAGPool	Accuracy 80.36%	Multi-hop Attention-based Graph Pooling: A Personalized PageRank Perspective 2024-03-04	코드 1
UGT	Accuracy 80.12 ±0.32	Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity 2023-08-18	코드 1 · 코드 2 · 코드 3
U2GNN (Unsupervised)	Accuracy 80.01%	Universal Graph Transformer Self-Attention Networks 2019-09-26	코드 1
sGIN	Accuracy 78.97%	Mutual Information Maximization in Graph Neural Networks 2019-05-21	코드 1 · 코드 2
QS-CNNs (Quantum Walk)	Accuracy 78.80%	Quantum-based subgraph convolutional neural networks 2019-04-01	연결 없음
WKPI-kmeans	Accuracy 78.8%	Learning metrics for persistence-based summaries and applications for graph classification 2019-04-27	코드 1
PIN	Accuracy 78.8%	Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes 2023-08-13	연결 없음
hGANet	Accuracy 78.65%	Graph Representation Learning via Hard and Channel-Wise Attention Networks 2019-07-05	코드 1
U2GNN	Accuracy 78.53%	Universal Graph Transformer Self-Attention Networks 2019-09-26	코드 1
DS-CNNs (Random Walk)	Accuracy 78.35%	Quantum-based subgraph convolutional neural networks 2019-04-01	연결 없음
cGANet	Accuracy 78.23%	Graph Representation Learning via Hard and Channel-Wise Attention Networks 2019-07-05	코드 1
CAN	Accuracy 78.2%	Cell Attention Networks 2022-09-16	코드 1
GANet	Accuracy 77.92%	Graph Representation Learning via Hard and Channel-Wise Attention Networks 2019-07-05	코드 1
GraphStar	Accuracy 77.90%	Graph Star Net for Generalized Multi-Task Learning 2019-06-21	코드 1
NERO	Accuracy 77.89%	Relation order histograms as a network embedding tool 2021-06-09	코드 1
Fea2Fea-s2	Accuracy 77.8%	Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks 2021-06-24	코드 1
DGA	Accuracy 77.71%	Discriminative Graph Autoencoder 2018-11-17	연결 없음
Graph U-Nets	Accuracy 77.68%	Graph U-Nets 2019-05-11	코드 1 · 코드 2 · 코드 3
GATv2	Accuracy 77.679±2.187	How Attentive are Graph Attention Networks? 2021-05-30	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8
PNA	Accuracy 77.679±3.281	Principal Neighbourhood Aggregation for Graph Nets 2020-04-12	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8
GIC	Accuracy 77.65%	Gaussian-Induced Convolution for Graphs 2018-11-11	연결 없음