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Published July 9, 2025 | Version v1.6.1
Software Open

APPFL: Advanced Privacy-Preserving Federated Learning

Authors/Creators

  • 1. Argonne National Laboratory
  • 2. ExxonMobil Technology and Engineering Company
  • 3. University of Illinois at Urbana-Champaign
  • 4. University of California, Santa Cruz
  • 5. University of Cambridge

Description

New Features

  • Add documentation for CADRE (Customizable Assurance of Data Readiness) modules
  • Add tutorials for running APPFL on FLamby datasets, both on AWS and HPCs
  • Add tutorials for Globus-based authentication

Notes

If you use this software, please cite it using the metadata from this file.

Files

APPFL/APPFL-v1.6.1.zip

Files (6.1 MB)

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md5:bd2446a0b3b041c5c579a0475aee75ee
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Additional details

Related works

Is supplement to
Software: https://github.com/APPFL/APPFL/tree/v1.6.1 (URL)

Software

Repository URL
https://github.com/APPFL/APPFL