capeprivacy / tf-world-tutorialLinks
TensorFlow World 2019 Tutorial: Privacy-Preserving Machine Learning with TF Encrypted & PySyft
☆46Updated 2 years ago
Alternatives and similar repositories for tf-world-tutorial
Users that are interested in tf-world-tutorial are comparing it to the libraries listed below
Sorting:
- A curated list of resources for privacy-preserving machine learning☆148Updated 4 years ago
- Various material around private machine learning, some associated with blog☆150Updated 6 years ago
- SOON TO BE DEPRECATED - The TensorFlow bindings for PySyft☆57Updated 5 years ago
- A set of tutorials to implement the Federated Averaging algorithm on TensorFlow.☆182Updated 4 years ago
- Collateral Learning - Functional Encryption and Adversarial Training on partially encrypted networks☆76Updated last year
- Bridge between TensorFlow and the Microsoft SEAL homomorphic encryption library☆95Updated 5 years ago
- Secure collaborative training and inference for XGBoost.☆105Updated 3 years ago
- A library for running Functional Encryption on tensors☆45Updated 4 years ago
- A concise primer on Differential Privacy☆29Updated 5 years ago
- A SMPC companion library for Syft☆105Updated last week
- Repository with tutorials and applications of Private-AI algorithms with PySyft☆73Updated 6 years ago
- tf-trusted allows you to run TensorFlow models in secure enclaves☆87Updated 5 years ago
- Privacy-preserving XGBoost Inference☆49Updated 2 years ago
- Privacy -preserving Neural Networks☆79Updated 6 years ago
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 5 years ago
- Defines types for all Serde encoding across languages☆20Updated last year
- A Secure Multiparty Computation (MPC) protocol for computing linear regression on vertically distributed datasets.☆32Updated 6 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆276Updated last year
- SOON TO BE DEPRECATED - Private machine learning progress☆471Updated 5 years ago
- nGraph-HE: Deep learning with Homomorphic Encryption (HE) through Intel nGraph☆223Updated 2 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- This repository is a fork of Microsoft Research's homomorphic encryption implementation, the Simple Encrypted Arithmetic Library (SEAL). …☆230Updated 6 years ago
- A curated list of resources dedicated to federated learning.☆104Updated 3 years ago
- 6.857 project - implementation of scheme for encrypting integer vectors that allows addition, linear transformation, and weighted inner p…☆70Updated 8 years ago
- A privacy-preserving app for comparing last-known locations of coronavirus patients☆43Updated 2 years ago
- News in Privacy-Preserving Machine Learning☆12Updated 5 years ago
- Code for NIPS'2017 paper☆51Updated 5 years ago
- ☆436Updated last year
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆538Updated last week
- A Simulator for Privacy Preserving Federated Learning☆96Updated 4 years ago