https://github.com/Abigale001/FairDGE
공식 코드Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach
Papers with Code 아카이브
Graph Mining
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Ahren09/CODER
공식 코드https://github.com/GraphEmbedding/FEM
공식 코드Mathematics Content Understanding for Cyberlearning via Formula Evolution Map
https://github.com/IlyaTyagin/AGATHA-C-GP
공식 코드Accelerating COVID-19 research with graph mining and transformer-based learning
https://github.com/Oxfordblue7/GCFL
공식 코드https://github.com/RManLuo/CP-GNN
공식 코드Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model
https://github.com/RingBDStack/AGE
공식 코드A Robust and Generalized Framework for Adversarial Graph Embedding
https://github.com/Wangyuwen0627/GIP-Framework
공식 코드Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks
https://github.com/Wayfear/Coacher
공식 코드Zero-Shot Scene Graph Relation Prediction through Commonsense Knowledge Integration
https://github.com/YingtongDou/CARE-GNN
공식 코드Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
https://github.com/YuanchenBei/CorGCN
공식 코드Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification
https://github.com/amazon-science/amazon-RTRExtractor
공식 코드Covering a Graph with Dense Subgraph Families, via Triangle-Rich Sets
https://github.com/benedekrozemberczki/datasets
공식 코드Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs
https://github.com/benedekrozemberczki/karateclub
공식 코드Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs
https://github.com/benedekrozemberczki/tigerlily
공식 코드TigerLily: Finding drug interactions in silico with the Graph
https://github.com/buet-gd/Deep-DynaResGCN-community
공식 코드Overlapping Community Detection using Dynamic Dilated Aggregation in Deep Residual GCN
https://github.com/buguemar/grtc_gnns
공식 코드https://github.com/compstorylab/sirius
공식 코드Sirius: Visualization of Mixed Features as a Mutual Information Network Graph
https://github.com/corradomonti/learnable-opinion-dynamics
공식 코드https://github.com/cspjiao/RONE
공식 코드https://github.com/doujiang-zheng/tip-gnn
공식 코드Transition Propagation Graph Neural Networks for Temporal Networks
https://github.com/edisonleeeee/magi
공식 코드Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective
https://github.com/ewhlee/pgb
공식 코드PGB: A PubMed Graph Benchmark for Heterogeneous Network Representation Learning
https://github.com/fedego/fedego
공식 코드FedEgo: Privacy-preserving Personalized Federated Graph Learning with Ego-graphs
https://github.com/gongyguo/ANCKA
공식 코드A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation
https://github.com/hamedn/SliceNDice
공식 코드SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view Graphs
https://github.com/hkust-knowcomp/privategraphencoder
공식 코드Independent Distribution Regularization for Private Graph Embedding
https://github.com/hyperbard/hyperbard
공식 코드https://github.com/hyperbard/tutorials
공식 코드https://github.com/jhl-hust/nagphormer
공식 코드NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs
https://github.com/jhonygiraldo/S2-GNN
공식 코드Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks
https://github.com/jisungyoon/persona2vec
공식 코드Persona2vec: A Flexible Multi-role Representations Learning Framework for Graphs
https://github.com/jjzhou012/I2BGNN
공식 코드https://github.com/joey001/kplex_degen_gap
공식 코드Fast Maximum $k$-Plex Algorithms Parameterized by Small Degeneracy Gaps
https://github.com/junhongmit/H2GB
공식 코드When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark
https://github.com/laclauc/fairness-graph
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.