There are 1 repository under ppml topic.
Concrete ML: Privacy Preserving ML framework built on top of Concrete, with bindings to traditional ML frameworks.
R package that provides estimation methods for Gravity Models
Samples of multi-class text classification with Differential Privacy Tensorflow 2.0
A compiled list of resources and materials for PPML
Hands-on part of the Federated Learning and Privacy-Preserving ML tutorial given at VISUM 2022
Sisyphus: A Cautionary Tale of Using Polynomial Activations in Privacy-Preserving Deep Learning
Extension of the MOTION2NX framework to implement neural network inferencing task where the data is supplied to the “secure compute servers” by the “data providers”.
A Learning Journal on (Privacy-Preserving) AI for Medicine and Healthcare
Learn how to apply core privacy principles and techniques to the data science and machine learning workflows with Python open source libraries for privacy-preserving machine learning.
A C++-based framework for privacy-preserving machine learning using HE and TEE
Health Score model implementation using Homomorphic Encryption to preserve data privacy.
A Replication (and Tribute) of The Log of Gravity