wuyucheng2002 / CTAug
Code for "Graph Contrastive Learning with Cohesive Subgraph Awareness"
☆14Updated last year
Alternatives and similar repositories for CTAug:
Users that are interested in CTAug are comparing it to the libraries listed below
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- ☆47Updated 2 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆32Updated 2 years ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆30Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆28Updated 11 months ago
- ☆37Updated 3 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated last year
- NeurIPS 2022 - SHGP☆31Updated last year
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆42Updated 2 years ago
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆25Updated 2 months ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 3 years ago
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆30Updated last year
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆103Updated last year
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆11Updated 6 months ago
- The source code of SpCo☆35Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- ☆26Updated 2 years ago
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆19Updated 2 years ago
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated last year
- Neighbor Contrastive Learning on Learnable Graph Augmentation☆36Updated 10 months ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 10 months ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆35Updated 3 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆44Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆80Updated 5 months ago