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FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural
  Network in Analyzing Geospatial Resilience of Multicommodity Food Flows

FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows

20 October 2023
Yuxiao Qu
Jinmeng Rao
Song Gao
Qianheng Zhang
Wei-Lun Chao
Yu-Chuan Su
Michelle Miller
Alfonso Morales
Patrick Huber
    FedML
ArXivPDFHTML

Papers citing "FLEE-GNN: A Federated Learning System for Edge-Enhanced Graph Neural Network in Analyzing Geospatial Resilience of Multicommodity Food Flows"

3 / 3 papers shown
Title
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing
  in the Agri-Food Sector
The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector
A. Durrant
Milan Markovic
David Matthews
David May
J. Enright
Georgios Leontidis
FedML
53
69
0
14 Apr 2021
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning
Hong-You Chen
Wei-Lun Chao
FedML
54
260
0
04 Sep 2020
Federated Optimization: Distributed Machine Learning for On-Device
  Intelligence
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konecný
H. B. McMahan
Daniel Ramage
Peter Richtárik
FedML
124
1,895
0
08 Oct 2016
1