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#

privacy-preserving-machine-learning

Here are 104 public repositories matching this topic...

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

  • UpdatedMay 30, 2024

Training PyTorch models with differential privacy

  • UpdatedJun 30, 2025
  • Jupyter Notebook
PrivacyRaven

Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.

  • UpdatedOct 3, 2023
  • Python

Advanced Privacy-Preserving Federated Learning framework

  • UpdatedJul 16, 2025
  • Python

Implementation of protocols in SecureNN.

  • UpdatedOct 8, 2022
  • C++

Fast, memory-efficient, scalable optimization of deep learning with differential privacy

  • UpdatedMay 19, 2025
  • Python

Piranha: A GPU Platform for Secure Computation

  • UpdatedApr 2, 2023
  • C++

This is the research repository for Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition.

  • UpdatedJun 21, 2022
  • Python

GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)

  • UpdatedJul 3, 2023
  • Jupyter Notebook

Privacy Preserving Convolutional Neural Network using Homomorphic Encryption for secure inference

  • UpdatedFeb 3, 2021
  • C++

[ICML 2022 / ICLR 2024] Source code for our papers "Plug & Play Attacks: Towards Robust and Flexible Model Inversion Attacks" and "Be Careful What You Smooth For".

  • UpdatedAug 7, 2024
  • Jupyter Notebook

This repository contains all the implementation of different papers on Federated Learning

  • UpdatedAug 12, 2020
  • Jupyter Notebook

Secure Linear Regression in the Semi-Honest Two-Party Setting.

  • UpdatedOct 1, 2019
  • C++

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