Official implementation of the paper "Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity"

Flower tutorial repository for PyCon DE & PyData 2025 talk "The Future of AI is Federated"

Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration

Federated Pix2Pix Training with NVIDIA FLARE

machine learning for blockchain

Basic federated learning pipeline using Flower and scikit‑learn on autism dataset.

Federated Learning on MNIST by combining local models from clean and noisy clients with FedAvg to boost overall accuracy

Mimir: Collaborative LLM inference where secrets stay secret. Combines Multiparty Computation (MPC) and Trusted Execution Environments (TEEs) to run autoregressive models across mutually distrustful parties without revealing prompts or weights.

Project ALVI

A research-oriented federated learning framework implemented with pytorch and WandB.