Here are
16 public repositories
matching this topic...
Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)
Updated
Feb 9, 2025
Python
Securing Collaborative Medical AI by Using Differential Privacy
Updated
Jan 17, 2024
Python
Easy-to-use utilities to build privacy-preserving AI.
Updated
Jun 27, 2025
Python
Code for the paper "PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning" by L. Corbucci, M. A. Heikkilä, D.S. Noguero, A. Monreale, N. Kourtellis.
Updated
May 19, 2025
Python
Building an AI model for chest X-ray under patient privacy guarantees
Updated
Feb 27, 2024
Python
Hands-on part of the Federated Learning and Privacy-Preserving ML tutorial given at VISUM 2022
Updated
Jul 22, 2022
Python
A differentially private spiking neural network with temporal enhanced pooling
Updated
May 3, 2024
Jupyter Notebook
A Comparative Study of Gradient Clipping Techniques in Differentially Private Stochastic Gradient Descent (DP-SGD)
Updated
Jun 13, 2024
Python
The extension library of Pytorch Opacus which enables fast and efficient DP-SGD training via example-wise gradient computation
Updated
Dec 23, 2022
Cuda
In this project we add differential privacy into an openset recognizer.to implement DP we use opacus library.
Updated
Jul 9, 2023
Jupyter Notebook
Imagenet-scale DP-SGD training using Pytorch Opacus
Updated
Nov 14, 2022
Python
[Tutorials] Privacy Preserving MedMNIST Benchmarking.
Updated
Mar 3, 2025
Jupyter Notebook
Intrusion Detection with Differential Privacy using Opacus on the UNSW-NB15 dataset
Updated
May 13, 2025
Jupyter Notebook
Updated
Mar 11, 2025
Python
Implementation of Opacus DP in Flower.
Updated
Oct 28, 2024
Python
Implement differentially-private SGD on MLP classifier. Tested on MNIST dataset. For large privacy (ε), accuracy% decreases (down 97% --> 91%).
Updated
Jun 16, 2025
Jupyter Notebook
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