yanliang3612 / ReVarLinks
Code for Revar, NeurIPS 2023.
☆12Updated 4 months ago
Alternatives and similar repositories for ReVar
Users that are interested in ReVar are comparing it to the libraries listed below
Sorting:
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆43Updated 2 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"☆15Updated last year
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆31Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated 2 years ago
- Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models☆10Updated 2 weeks ago
- [IJCAI'23] LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity☆17Updated 10 months ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆44Updated 3 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆42Updated 2 years ago
- Code for ICML 2023 paper "Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs"☆20Updated 2 years ago
- code for kdd feasibiiity☆12Updated 2 years ago
- A curated list of papers and code related to class-imbalanced learning on graphs (CILG).☆42Updated 8 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆34Updated 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
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- ICLR25_Unifying Unsupervised Graph-Level Out-of-Distribution Detection and Anomaly Detection: A Benchmark☆59Updated last month
- ☆12Updated 2 years ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆92Updated 3 months ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- ☆59Updated 10 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated last year
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆23Updated 2 years ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- [CIKM 2023] Code for the paper "LTE4G: Long-Tail Experts for Graph Neural Networks"☆40Updated 3 years ago
- The official source code for "Class Label-aware Graph Anomaly Detection", accepted at CIKM 2023.☆16Updated 2 years ago
- Code for AAAI 2023 (Oral) paper "Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effe…☆26Updated last year
- [NeurIPS'23] Towards Self-Interpretable Graph-Level Anomaly Detection☆26Updated last year