rwilliamspbg-ops/Sovereign_Map_Federated_Learning
Sovereign Map is a Byzantine-tolerant Federated Learning framework for edge and mesh networks. Powered by the Mohawk Protocol, it uses a streaming architecture to achieve a 224x memory reduction, enabling secure orchestration of 100M+ nodes via TPM 2.0 hardware-rooted trust.
Stars
1
Forks
—
Language
Go
License
MIT
Category
Last pushed
Mar 19, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rwilliamspbg-ops/Sovereign_Map_Federated_Learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
flwrlabs/flower
Flower: A Friendly Federated AI Framework
zama-ai/concrete-ml
Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on...
p2pfl/p2pfl
P2PFL is a decentralized federated learning library that enables federated learning on...
JonasGeiping/breaching
Breaching privacy in federated learning scenarios for vision and text
SMILELab-FL/FedLab
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.