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:
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆61Updated 2 years ago
- Dynamic Graph Benchmark☆83Updated 2 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆71Updated 3 years ago
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆82Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 4 months ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆60Updated 3 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated 2 years ago
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"☆34Updated 3 years ago
- ☆19Updated 2 years ago
- [ICML 2023] Linkless Link Prediction via Relational Distillation☆24Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆90Updated 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
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated 2 years 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
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆142Updated 2 weeks ago
- [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…☆54Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆45Updated 3 years ago
- ☆75Updated 3 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆114Updated last year
- ☆90Updated 2 years ago