A federated graph learning method to realize multi-party collaboration for molecular discovery
LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).Article Google Scholar Abramson, J. et al. Accurate...
federated
Decentralized Federated Learning Enables Privacy-Preserving Computer Vision On Edge Devices
The increasing reliance on machine learning introduces significant privacy concerns as collaborative model training often requires access to sensitive data....
Quantum Federated Learning Framework Safeguards Data And Models With Multi-layered Privacy Protocols And Maintains Training Efficiency
Federated Learning offers a powerful new approach to distributed machine learning, harnessing the collective processing power of numerous devices while...
Federated multi scale vision transformer with adaptive client aggregation for industrial defect detection
The proposed Federated Multi-Scale Vision Transformer with Adaptive Client Aggregation (Fed-MSVT) is a novel federated learning-based defect detection framework for...
A fused weighted federated learning-based adaptive approach for early-stage drug prediction
The primary concern of machine vision in assisting physicians and patients is the early-stage prediction of drugs and monitoring to...
HtFLlib: A Unified Benchmarking Library for Evaluating Heterogeneous Federated Learning Methods Across Modalities
AI institutions develop heterogeneous models for specific tasks but face data scarcity challenges during training. Traditional Federated Learning (FL) supports...
