kaize0409/awesome-few-shot-gnn kaize0409/awesome-few-shot-gnn

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kaize0409/awesome-few-shot-gnn
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An index of algorithms for few-shot learning/meta-learning on graphs

Graph Meta-Learning/Graph Few-Shot Learning Awesome

The repository contains links primarily to conference and journal publications about graph meta-learning and graph few/zero-shot learning. You are encouraged to contribute to this repo!

Check out our survey: [IJCAI'22] Few-shot learning on graphs

Node-level Task

Name Paper Code
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
MetaTNE [NuerIPS 2020] Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding PyTorch
M3S [AAAI 2020] Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes TensorFlow
RALE [AAAI 2021] Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph TensorFlow
Meta-GDN [WWW 2021] Few-shot Network Anomaly Detection via Cross-network Meta-learning PyTorch
Mixup [WWW 2021] Mixup for Node and Graph Classification [N/A]
HAG-Meta [WSDM 2022] Graph few-shot class-incremental learning PyTorch
AutoGRL [IJCNN 2022] Automated Graph Representation Learning for Node Classification PyTorch
MuL-GRN [TKDE 2022] MuL-GRN: Multi-Level Graph Relation Network for Few-Shot Node Classification [N/A]
Meta-GPS [SIGIR 2022] Few-shot Node Classification on Attributed Networks with Graph Meta-learning [N/A]
TENT [SIGKDD 2022] Task-Adaptive Few-shot Node Classification PyTorch
KnowPrompt [WWW 2022] KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction PyTorch
IA-FSNC [IJCAI 2022] Information Augmentation for Few-shot Node Classifcation [N/A]
SGCL [ECML 2022] Supervised Graph Contrastive Learning for Few-shot Node Classification [N/A]
LADSL [Frontiers 2022] Few-shot node classification via local adaptive discriminant structure learning [N/A]
Meta-GIN [arXiv 2022] Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification [N/A]
LGLNN [NN 2022] LGLNN: Label Guided Graph Learning-Neural Network for few-shot learning [N/A]
TLP [LOG 2022] Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification PyTorch
TEG [KDD 2023] Task-Equivariant Graph Few-shot Learning PyTorch
VNT [KDD 2023] Virtual Node Tuning for Few-shot Node Classification [N/A]
COSMIC [KDD 2023] Contrastive Meta-Learning for Few-Shot Node Classification Pytorch
CGFL [CIKM 2023] Cross-heterogeneity Graph Few-shot Learning [N/A]
HPN [ICONIP 2023] Heterogeneous Graph Prototypical Networks for Few-Shot Node Classification [N/A]

Edge-level Task

Name Paper Code
GMatching [EMNLP 2018] One-Shot Relational Learning for Knowledge Graphs PyTorch
FSRL [AAAI 2019] Few-Shot Knowledge Graph Completion PyTorch
MetaR [EMNLP 2019] Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs PyTorch
FAAN [EMNLP 2020] Adaptive Attentional Network for Few-Shot Knowledge Graph Completion PyTorch
ZSGAN [AAAI 2020] Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs PyTorch
GEN [NeurIPS 2020] Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction PyTorch
CSR [NeurIPS 2022] Few-shot Relational Reasoning via Connection Subgraph Pretraining PyTorch
HiRe [ICLR 2023] Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion PyTorch
NP-FKGC [SIGIR 2023] Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion PyTorch
FLow-MV [KDD 2023] Few-Shot Low-Resource Knowledge Graph Completion with Multi-view Task Representation Generation [N/A]

Graph-level Task

Name Paper Code
GFL [AAAI 2020] Graph Few-Shot Learning via Knowledge Transfer [N/A]
G-META [NuerIPS 2020] Graph Meta Learning via Local Subgraphs PyTorch
AS-MAML [CIKM 2020] Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification PyTorch
Super-class [ICLR 2020] Few-shot learning on graphs via super-classes based on graph spectral measures PyTorch
Meta-MGNN [WWW2021] Few-Shot Graph Learning for Molecular Property Prediction PyTorch
MI-GNN [SIGIR 2021] Meta-Inductive Node Classification across Graphs PyTorch
CuCo [IJCAI 2021] CuCo: Graph Representation with Curriculum Contrastive Learning PyTorch
PAR [NeurIPS 2021] Property-Aware Relation Networks for Few-Shot Molecular Property Prediction PyTorch
GFL-RTG [TNNLS 2022] Graph Few-Shot Learning via Restructuring Task Graph [N/A]
FAITH [IJCAI 2022] FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs PyTorch
MB-FSGC [LoG 2022] Metric Based Few-Shot Graph Classification PyTorch
HSL-RG [NN 2023] Few-shot Molecular Property Prediction via Hierarchically Structured Learning on Relation Graphs [N/A]
CDTC [AAAI 2023] Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator [N/A]

Acknowledgement

This page is contributed and maintained by Kaize Ding ([email protected]), Sungwon Kim ([email protected]), Donato Crisostomi ([email protected]), Zhen Tan ([email protected]), and Song Wang ([email protected]).

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