Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification [LoG 2022] [Paper]

Dataset

[Pytorch Link]

Sufficient number of classes: A. CoraFull B. Coauthor-CS C. Ogbn-Arxiv

Insufficient number of classes: D. Cora E. CiteSeer, F. Amazon-Computer

Methods

Meta-learning

Full Paper List

Name	Paper	Original Code
MAML	[ICML 2017] Model-agnostic Meta-learning for Fast Adaptation of Deep Networks	PyTorch
ProtoNet	[NeurIPS 2017] Prototypical Networks for Few-shot Learning	PyTorch
Meta-GNN	[CIKM 2019] Meta-GNN: On Few-shot Node Classification in Graph Meta-learning	PyTorch
GPN	[CIKM 2020] Graph Prototypical Networks for Few-shot Learning on Attributed Networks	PyTorch
AMM-GNN	[CIKM 2020] Graph Few-shot Learning with Attribute Matching	[N/A]
G-Meta	[NeurIPS 2020] Graph Meta Learning via Local Subgraphs	PyTorch
TENT	[SIGKDD 2022] Task-Adaptive Few-shot Node Classification	PyTorch

Contrastive Learning for TLP

Full Paper List

Name	Paper	Original Code
FT-GNN	[ECCV 2020] Rethinking few-shot image classification: a good embedding is all you need?	PyTorch
MVGRL	[ICML 2020] Contrastive Multi-View Representation Learning on Graphs	PyTorch
GRACE	[ICML 2020 Workshop] Deep Graph Contrastive Representation Learning	PyTorch
GraphCL	[NeurIPS 2020] Graph Contrastive Learning with Augmentations	PyTorch
MERIT	[IJCAI 2021] Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning	PyTorch
BGRL	[ICLR 2022] LARGE-SCALE REPRESENTATION LEARNING ON GRAPHS VIA BOOTSTRAPPING	PyTorch
SUGRL	[AAAI 2022] Simple Unsupervised Graph Representation Learning	PyTorch

Running Time on Cora

Methods	MAML	ProtoNet	Meta-GNN	GPN	AMM-GNN	G-Meta	TENT	MVGRL	GraphCL	Grace	MERIT	SUGRL
Time (s)	9.89	2.99	28.30	4.79	42.45	50.78	35.37	90.40	55.57	11.62	869.56	7.17

Citation

@inproceedings{tantransductive,
  title={Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification},
  author={Tan, Zhen and Wang, Song and Ding, Kaize and Li, Jundong and Liu, Huan},
  booktitle={Learning on Graphs Conference}
}