kaize0409 / awesome-few-shot-gnnLinks
An index of algorithms for few-shot learning/meta-learning on graphs
☆155Updated 7 months ago
Alternatives and similar repositories for awesome-few-shot-gnn
Users that are interested in awesome-few-shot-gnn are comparing it to the libraries listed below
Sorting:
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 2 months ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- ☆38Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆31Updated last year
- ☆139Updated 2 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆70Updated 2 years ago
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆46Updated 3 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆65Updated 2 years ago
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 3 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆116Updated last year
- A curated list of papers and code related to class-imbalanced learning on graphs (CILG).☆43Updated 10 months ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆94Updated 6 months ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆105Updated 5 months ago
- A curated list of graph data augmentation papers.☆314Updated last year
- Pytorch Implementation of LoG 22 [Oral] -- Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification☆17Updated 2 years ago
- ☆99Updated 4 years ago
- Papers about out-of-distribution generalization on graphs.☆168Updated 2 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆61Updated 3 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆92Updated 4 years ago
- DGL Implementation of ICML 2020 Paper 'Contrastive Multi-View Representation Learning on Graphs'☆68Updated last year
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆94Updated 3 years ago
- ☆68Updated 2 years ago
- official code for our KDD21 paper "Adaptive Transfer Learning on Graph Neural Networks"☆43Updated 3 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 3 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆172Updated last year
- How Powerful are Spectral Graph Neural Networks☆74Updated 2 years ago