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LIT-1809: POT: Python Optimal Transport

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Properties4
StatusActive — read in full 2026-10-29 (NOTE-1325); the citable description of the POT library as of 2021. Worth citing for the library, with the version used, but not for fused or partial Gromov–Wasserstein or co-optimal transport, which this paper does not describe.
Version2
Tagsmathematics, anthology-candidate
Cited as “paper” byNOTE-1325 — Flamary et al. — POT

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Flamary, R., Courty, N., Gramfort, A., et al. (2021). POT: Python optimal transport. Journal of Machine Learning Research, 22(78), 1–8.

Read in full in NOTE-1325.

Key takeaways

  • A citable description of the library, its solvers and its engineering; no results and no benchmarks.
  • What POT offers depends on the version; this paper fixes the 2021 set.

Why this is here

Named by A5 and A6 as the tool for every transport arm of CASE-185: GW, fused and partial GW, and co-optimal transport (ot.coot). Registered as the paper that stands for the software.

The paper covers less than that. It names GW and partial OT, not fused GW, partial GW or ot.coot, which later releases added. For those arms the methods’ own papers (LIT-1813, LIT-1804) and the POT version used should be cited beside this one (NOTE-1325).

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