WANGBohaO-jpg / DR-GNN
[WWW2024] The official code for paper "Distributionally Robust Graph-based Recommendation System"
☆26Updated 10 months ago
Alternatives and similar repositories for DR-GNN:
Users that are interested in DR-GNN are comparing it to the libraries listed below
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆36Updated last year
- Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs☆30Updated 4 months ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆63Updated 10 months ago
- Code for AAAI'24 paper "Rethinking Graph Masked Autoencoders through Alignment and Uniformity”.☆13Updated 9 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".☆28Updated 10 months ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆26Updated 2 years ago
- Awesome Deep Group Recommendation is a collection of SOTA, novel deep group recommendation methods (papers, codes, and datasets).☆39Updated 5 months ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆16Updated last year
- The code of ICLR 2024 paper: Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective☆11Updated 10 months ago
- The source code of SpCo☆35Updated last year
- TheWebConf'24 full paper - "Linear-Time Graph Neural Networks for Scalable Recommendations"☆17Updated 5 months ago
- ☆55Updated 4 months ago
- Papers about out-of-distribution generalization on graphs.☆166Updated last year
- TransGNN, SIGIR 2024☆45Updated 8 months ago
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆80Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆28Updated last year
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆20Updated last year
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- Code for SGDD☆24Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆54Updated last year
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆10Updated 5 months ago
- [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆24Updated 5 months ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆86Updated 2 years ago
- The official pytorch implementation of Propagation_then_Training for graph (https://arxiv.org/abs/2010.12408)☆26Updated 3 years ago
- ☆19Updated 3 years ago
- Benchmark☆96Updated 11 months ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆102Updated last year
- ☆22Updated 6 months ago