#07 Which Federated Learning Framework
Sharing which federated learning framework we work with and why.
After exploring the what, how, and why of FL, let’s answer a crucial question:
Which framework should you choose for your federated learning projects?
Study Results: Flower Takes the Lead
A comprehensive study comparing 15 open-source FL frameworks across 15 evaluation criteria revealed Flower as the clear winner, scoring an impressive 84.75%! More here.
Why We’re Choosing Flower
Top-Tier Partnerships: Collaborations with NVIDIA, Google, AWS, Intel, and Mozilla, to name a few.
Cutting-Edge Methods: Quick adoption of newly published optimisation techniques.
Beyond Basic FL: Supports additional methods like differential privacy.
Reproducibility Focus: Runs a 3-month community sprint to improve reproducibility in FL with the goal of creating 50 high-quality baselines.
Thriving Ecosystem: The growing community of developers and adopters thanks to its open-source and user-focused, and friendly approach.
At AI4Cosmetics, we are pioneering the use of federated learning for chemical safety assessment. Our goal is to help the industry with more accurate in silico predictions (not outside of the applicability domain) and regulatory-ready evidence. Our proof-of-concept use cases have already shown promising results, and we are now ready to bring them into real-world applications.
If this challenge resonates with you, we’d love to hear from you and join the consortium. We also offer bespoke workshops and can assist in setting up your federated models.
We gratefully acknowledge the Flower Pilot Program and the feasibility grant MKB Innovatiestimulering Topsectoren (MIT) Noord-Holland for their support in advancing our research.
It's interesting how clearly Flower emerged as the frontrunner in your detailed comparison. I truely appreciate the depth of research you've put into this. For me, the focus on reproducibility and capabilities like differential privacy are crucial for wider adoption and trust in FL, especially in sensitive areas like chemical safety.