ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2404.01517
  4. Cited By
Addressing Heterogeneity in Federated Load Forecasting with
  Personalization Layers

Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers

1 April 2024
Shourya Bose
Yu Zhang
Kibaek Kim
ArXivPDFHTML

Papers citing "Addressing Heterogeneity in Federated Load Forecasting with Personalization Layers"

2 / 2 papers shown
Title
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework
Zilinghan Li
Shilan He
Ze Yang
Minseok Ryu
Kibaek Kim
Ravi K. Madduri
FedML
66
7
0
17 Sep 2024
A Secure Federated Learning Framework for Residential Short Term Load
  Forecasting
A Secure Federated Learning Framework for Residential Short Term Load Forecasting
Muhammad Akbar Husnoo
A. Anwar
N. Hosseinzadeh
S. Islam
A. N. Mahmood
R. Doss
70
34
0
29 Sep 2022
1