eaglelab-zju / NoisyGL
A Comprehensive Benchmark for Graph Neural Networks under Label Noise
☆12Updated 2 weeks ago
Related projects ⓘ
Alternatives and complementary repositories for NoisyGL
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆41Updated 2 years ago
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 2 years ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆22Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 2 years ago
- [ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改善类别不平衡节点分类☆20Updated 5 months ago
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆34Updated last year
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆28Updated 8 months ago
- Wiener Graph Deconvolutional Network Improves Self-Supervised Learning in AAAI 2023☆17Updated 7 months ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆35Updated last year
- ☆15Updated 9 months ago
- A curated list of papers and code related to class-imbalanced learning on graphs (CILG).☆32Updated 9 months ago
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 2 years ago
- Pytorch Implementation of LoG 22 [Oral] -- Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification☆14Updated last year
- ☆37Updated 2 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆38Updated last year
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆54Updated last year
- Graph based Knowledge Distillation: A Survey☆59Updated last year
- Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)☆120Updated last year
- Code for Neurips2021 Paper "Topology-Imbalance Learning for Semi-Supervised Node Classification".☆55Updated 3 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆32Updated 2 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆49Updated 2 years ago
- The code of “Prototypical Graph Contrastive Learning”. [TNNLS 2022]☆24Updated 2 years ago
- Python implementation of "Unsupervised Domain Adaptive Graph Convolutional Networks", WWW-20.☆55Updated 3 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆18Updated last week
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated 11 months ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆31Updated 2 years ago
- Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)☆22Updated 2 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆46Updated last year
- Code for "Graph Contrastive Learning with Cohesive Subgraph Awareness"☆13Updated 8 months ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆54Updated last year