zhao-tong / SDM2023_Graph_Data_Augmentation_TutorialLinks
Materials for SDM 2023 tutorial: Augmentation Methods for Graph Learning
☆21Updated 2 years ago
Alternatives and similar repositories for SDM2023_Graph_Data_Augmentation_Tutorial
Users that are interested in SDM2023_Graph_Data_Augmentation_Tutorial are comparing it to the libraries listed below
Sorting:
- Dynamic Graph Benchmark☆82Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆60Updated 2 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆70Updated 3 years ago
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆34Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆104Updated 2 months ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- ☆47Updated last year
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆97Updated last year
- ☆90Updated last year
- ☆19Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆81Updated 2 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆113Updated 11 months ago
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- [WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction☆48Updated 9 months ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- [ICML 2023] Linkless Link Prediction via Relational Distillation☆24Updated last year
- GLASS: GNN with Labeling Tricks for Subgraph Representation Learning☆31Updated 2 years ago
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆39Updated last year
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…☆54Updated 2 years ago
- [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"☆140Updated 9 months ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- ☆129Updated 4 months ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Pytorch implementation for ICLR24:"Online GNN Evaluation Under Test-Time Graph Distribution Shifts"☆16Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆106Updated last year
- An index of algorithms for few-shot learning/meta-learning on graphs☆157Updated 3 months ago