kaize0409 / awesome-few-shot-gnnLinks
An index of algorithms for few-shot learning/meta-learning on graphs
☆156Updated 4 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:
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 10 months ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs☆137Updated 2 years ago
- Code for paper https://arxiv.org/abs/2102.13186☆43Updated 4 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆69Updated last year
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 3 years ago
- The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"☆76Updated 3 years ago
- Papers about out-of-distribution generalization on graphs.☆167Updated 2 years ago
- ☆67Updated 2 years ago
- ☆135Updated 2 years ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆92Updated 3 months ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆42Updated 2 years ago
- A curated list of papers and code related to class-imbalanced learning on graphs (CILG).☆42Updated 8 months ago
- A curated list of graph data augmentation papers.☆312Updated last year
- ☆97Updated 4 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Updated 2 years ago
- ☆59Updated 10 months ago
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆43Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆85Updated 10 months ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆31Updated last year
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆89Updated 3 years ago
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 4 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆61Updated 2 years ago
- ☆38Updated 2 years ago
- ☆55Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 4 years ago