mims-harvard / GNNDeleteLinks
General Strategy for Unlearning in Graph Neural Networks
☆46Updated 2 years ago
Alternatives and similar repositories for GNNDelete
Users that are interested in GNNDelete are comparing it to the libraries listed below
Sorting:
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆20Updated 2 years ago
- ☆18Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆29Updated 3 years ago
- ☆26Updated 3 years ago
- Label-free Node Classification on Graphs with Large Language Models (LLMS)☆87Updated 2 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- Papers about out-of-distribution generalization on graphs.☆168Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆65Updated 2 years ago
- ☆131Updated 8 months ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated 2 years ago
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆47Updated 11 months ago
- A collection of papers on Graph Structural Learning (GSL)☆57Updated last year
- Paper List for Fair Graph Learning (FairGL).☆142Updated last year
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆12Updated last year
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆42Updated last year
- The official implement of NeurIPS'24 Datasets and Benchmarks Track paper: GLBench: A Comprehensive Benchmark for Graphs with Large Langua…☆68Updated last year
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆118Updated 2 years ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆35Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆94Updated 3 years ago
- Code for SGDD☆26Updated 2 years ago
- Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms☆65Updated last year
- Official implementation of GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs☆62Updated 9 months ago
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated 2 months ago
- [ICML 2023] Linkless Link Prediction via Relational Distillation☆24Updated 2 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- code for kdd feasibiiity☆12Updated 2 years ago
- Code for paper https://arxiv.org/abs/2102.13186☆43Updated 4 years ago
- ☆102Updated 2 years ago
- A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…☆69Updated 2 years ago