Zhen-Tan-dmml / GFCILLinks
Pytorch Implementation of WSDM 2022 -- Graph Few-shot Class-incremental Learning
☆23Updated 3 years ago
Alternatives and similar repositories for GFCIL
Users that are interested in GFCIL are comparing it to the libraries listed below
Sorting:
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph☆13Updated 2 years ago
- Graph Few-Shot Class-Incremental Learning via Prototype Representation☆20Updated 2 years ago
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆25Updated 3 months ago
- Pytorch Implementation of LoG 22 [Oral] -- Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification☆17Updated 2 years ago
- ☆9Updated last year
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆42Updated 2 years ago
- ☆9Updated 3 years ago
- This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Lea…☆17Updated 2 years ago
- ☆16Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆41Updated 2 years ago
- GOODAT: Towards Test-time Graph Out-of-Distribution Detection☆11Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated 2 years ago
- ☆57Updated 6 months ago
- Implementation of CIKM2020 -- Graph Prototypical Networks for Few-shot Learning on Attributed Networks☆47Updated 4 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆89Updated 2 years ago
- The official source code for "Task-Equivariant Graph Few-shot Learning (TEG)" at KDD 2023.☆24Updated last year
- Python implementation of "Unsupervised Domain Adaptive Graph Convolutional Networks", WWW-20.☆56Updated 4 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆32Updated last year
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆23Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- [IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".☆40Updated 2 years ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated last year
- Streaming Graph Neural Networks via Continual Learning (CIKM 2020)☆43Updated 4 years ago
- A meta-learning framework for few-shot graph learning☆18Updated 2 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- The official source code for "GraFN: Semi-Supervised Node Classification on Graph with Few Labels via Non-Parametric Distribution Assignm…☆25Updated 2 years ago