We use Opacus from PyTorch and PySyft from OpenMined to combine Federated Learning with Differential Privacy.
Encrypted inference with ResNet-18 using PyTorch + PySyft on ants & bees images
CrypTen integrated in PySyft: a fast SMPC backend for secure computation between servers.
This post is part of our Privacy-Preserving Data Science, Explained Simply series.
“You would see hundreds and hundreds of unsolved crimes solved overnight,” Detective Michael Fields of the Orlando Police Department, from
We’re very excited to announce the next round of open-source software development grants in the OpenMined community, generously sponsored by
Encrypted Training of Deep Learning models with PyTorch + PySyft on MNIST
Encrypted Deep Learning Classification with PyTorch & PySyft in < 33ms on MNIST
Deep Learning -> Federated Learning in 10 Lines of PyTorch + PySyft
