FeGAN

FeGAN

Scaling distributed Generative Adversarial Networks (GANs)

The FeGAN system enables training GANs in the Federated Learning setup. GANs are generative adversarial networks, a class of machine learning where two neural networks contest with each other. FeGAN is implemented on PyTorch and is using less bandwidth and is faster than using stat-of-the-art GANs implementations.

Federated LearningPyTorch
Key facts
Maturity
PrototypeIntermediateMature
Support
C4DT
Inactive
Lab
Unknown
  • Technical
  • Research papers

Distributed Computing Lab

Distributed Computing Lab
Rachid Guerraoui

Prof. Rachid Guerraoui

The Distributed Computing Lab focuses currently on Scalable Implementations of Cryptocurrencies, Byzantine fault tolerance and privacy in distributed machine learning, distributed algorithms making use of RDMA and NVRAM.

This page was last edited on 2024-03-22.