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Subgraph Counting
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Studying and Improving Graph Neural Network-based Motif Estimation
BEACON: A Benchmark for Efficient and Accurate Counting of Subgraphs
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
Revisiting Graph Neural Networks on Graph-level Tasks: Comprehensive Experiments, Analysis, and Improvements
Discovering Motifs to Fingerprint Multi-Layer Networks: a Case Study on the Connectome of C. Elegans
Representation Learning for Frequent Subgraph Mining
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness
Communication Cost Reduction for Subgraph Counting under Local Differential Privacy via Hash Functions
On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
DeSCo: Towards Generalizable and Scalable Deep Subgraph Counting
The Expressive Power of Graph Neural Networks: A Survey
Improving Expressivity of Graph Neural Networks using Localization
Reinforcement Learning Enhanced Weighted Sampling for Accurate Subgraph Counting on Fully Dynamic Graph Streams
Evaluating Graph Generative Models with Contrastively Learned Features
Two-level Graph Neural Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.