daiquanyu / AdaGCN_TKDE
This paper studies the problem of cross-network node classification to overcome the insufficiency of labeled data in a single network. It aims to leverage the label information in a partially labeled source network to assist node classification in a completely unlabeled or partially labeled target network. Existing methods for single network lea…
☆25Updated 2 years ago
Alternatives and similar repositories for AdaGCN_TKDE:
Users that are interested in AdaGCN_TKDE are comparing it to the libraries listed below
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- ☆11Updated 3 years ago
- official code for our KDD21 paper "Adaptive Transfer Learning on Graph Neural Networks"☆42Updated 3 years ago
- Python implementation of "Unsupervised Domain Adaptive Graph Convolutional Networks", WWW-20.☆56Updated 3 years ago
- Unsupervised Domain Adaptation on Graphs☆15Updated 2 years ago
- [IJCAI'23] LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity☆17Updated 4 months ago
- Code source for Graph Transfer Learning project developed by Northeastern University's SPIRAL research group☆9Updated 3 years ago
- [IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".☆40Updated 2 years ago
- Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective☆24Updated last year
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆29Updated last year
- 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
- StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs☆22Updated last year
- Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning☆19Updated 11 months ago
- source code for TNNLS paper "Multi-Task Representation Learning with Multi-View Graph Convolutional Networks"☆19Updated 4 years ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- ☆39Updated last year
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆34Updated 2 years ago
- Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)☆23Updated 2 years ago
- ☆26Updated 3 years ago
- Reimplementation of AAAI21 paper "Beyond Low-frequency Information in Graph Convolutional Networks" based on PyTorch and PyTorch Geometri…☆22Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated 9 months ago
- Network Together: Node Classification via Cross-Network Deep Network Embedding☆11Updated 3 years ago
- Official Implementation of AdaGCN (ICLR 2021)☆61Updated 3 years ago
- Xiangguo Sun et al. Heterogeneous Hypergraph Embedding for Graph Classification, WSDM2021☆30Updated 4 years ago
- [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆24Updated 5 months ago
- Hypergraph convolution and attention networks research☆13Updated 8 months ago
- A meta-learning framework for few-shot graph learning☆18Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆77Updated 4 months ago
- The implementation for DropMessage.☆37Updated 2 years ago