A novel progressive training algorithm for learning Graph Neural Networks with Differential Privacy guarantees read more of ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees

Diffprivlib is a general-purpose library for experimenting with, investigating and developing applications in, differential privacy. read more of Diffprivlib: The IBM Differential Privacy Library

A tailored Graph Neural Network architecture with Differential Privacy guarantees for both training and inference. read more of GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation

Federated training of Graph Neural Networks (GNNs) with Local Differential Privacy read more of Locally Private Graph Neural Networks