thupchnsky / dp-gnnLinks
DP-GNN design that ensures both model weights and inference procedure differentially private (NeurIPS 2023)
☆12Updated last year
Alternatives and similar repositories for dp-gnn
Users that are interested in dp-gnn are comparing it to the libraries listed below
Sorting:
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆29Updated 2 years ago
- ☆29Updated 3 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆27Updated 2 years ago
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 2 years ago
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- ☆18Updated 3 years ago
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated 2 years ago
- LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation ICML_2023☆13Updated last year
- Pytorch implementation of EvenNet.☆20Updated 2 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- An Open and Unified Benchmark for Graph Condensation (submitted to NeurIPS 2024 Datasets and Benchmarks Track)☆18Updated 9 months ago
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆19Updated 2 years ago
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆48Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆32Updated last year
- ☆26Updated 2 years ago
- Code for ICLR'2021 paper: On Dyadic Fairness: Exploring and Mitigating Bias in Graph Connections☆12Updated 3 years ago
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- ☆20Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Ongoing project: a library for graph foundation model☆13Updated last year
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- ☆54Updated 8 months ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated last year
- Official Pytorch implementation of IJCAI'21 paper "GraphMI: Extracting Private Graph Data from Graph Neural Networks"☆13Updated 3 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆52Updated 2 years ago
- A curated list of resources for OOD detection with graph data.☆19Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- ☆14Updated 3 years ago