superallen13 / CaT-CGLLinks
☆16Updated 2 years ago
Alternatives and similar repositories for CaT-CGL
Users that are interested in CaT-CGL are comparing it to the libraries listed below
Sorting:
- ☆59Updated last year
- Graph Few-Shot Class-Incremental Learning via Prototype Representation☆21Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 3 years ago
- ☆10Updated last year
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆46Updated 3 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆44Updated 2 years ago
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆44Updated last year
- Code for The Web Conference 2022 Paper "Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding"☆17Updated 3 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆32Updated last year
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆28Updated last year
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆65Updated last year
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆94Updated 7 months ago
- Streaming Graph Neural Networks via Continual Learning (CIKM 2020)☆43Updated 4 years ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated 2 years ago
- The official source code for Similarity Preserving Adversarial Graph Contrastive Learning (SP-AGCL) at KDD 2023.☆23Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆45Updated 2 years ago
- A collection of papers on Graph Structural Learning (GSL)☆57Updated 2 years ago
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆46Updated last year
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆38Updated 2 years ago
- "GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection" in NeurIPS 2023☆137Updated last year
- Awesome literature on imbalanced learning on graphs☆74Updated last year
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆25Updated 2 years ago
- ☆31Updated 3 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆36Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆87Updated last year
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆34Updated 3 years ago
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆17Updated 2 years ago
- PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)☆25Updated 10 months ago
- ☆38Updated 3 years ago