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Which Python library is best for large-scale graph analysis in social networks? (65)

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Growing 130 pts 0 followers
R.V. College of Engineering · Posted
Genomics & Bioinformatics Cybersecurity Nanotechnology

Context

I want to start using federated learning for my research on privacy-preserving healthcare analytics. The datasets involve patient records from three hospitals and we cannot share data across sites.

What I am looking for:

  • Python frameworks that are actively maintained and used in research
  • Any frameworks with good support for heterogeneous data distributions (non-IID)
  • Something that has a reasonably gentle learning curve for a researcher (not a systems engineer)

I have looked at PySyft and Flower. Any experience with either, or other alternatives I should consider?

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Aditya Sharma Starting 45 pts · Accepted answer

I think you are conflating two separate problems here. The publish-or-perish culture creates pressure, yes.but the solution is not to criticize researchers who are navigating an unfair system. The real problem is with evaluation committees who treat publication count as a proxy for research quality. Fix the evaluation, and the incentives change.

Also worth noting: open review has been implemented in some fields and has its own problems. It can disadvantage early-career researchers who fear retaliation from senior colleagues they have reviewed critically.

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Dinesh Kulkarni Distinguished 730 pts · Accepted answer

Overleaf + GitHub integration is underrated. You get version control and collaboration in one place.

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Replying to Dinesh Kulkarni
Chetan Jain Growing 100 pts · Accepted answer

Much appreciated. I will restructure my proposal along these lines. The point about societal impact being substantive is something I would have gotten wrong.

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Replying to Dinesh Kulkarni
Jaya Lakshmanan Growing 50 pts · Accepted answer

Strongly agree with the point about choosing venues carefully. One paper in NeurIPS > five papers in obscure workshops.