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removed ot bar contribs -> only o.lp reorganisation in this PR
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README.md

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* [Co-Optimal Transport](https://pythonot.github.io/auto_examples/others/plot_COOT.html) [49] and
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[unbalanced Co-Optimal Transport](https://pythonot.github.io/auto_examples/others/plot_learning_weights_with_COOT.html) [71].
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* Fused unbalanced Gromov-Wasserstein [70].
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* OT Barycenters for generic transport costs [].
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POT provides the following Machine Learning related solvers:
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[72] Thibault Séjourné, François-Xavier Vialard, and Gabriel Peyré (2021). [The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation](https://proceedings.neurips.cc/paper/2021/file/4990974d150d0de5e6e15a1454fe6b0f-Paper.pdf). Neural Information Processing Systems (NeurIPS).
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[73] Séjourné, T., Vialard, F. X., & Peyré, G. (2022). [Faster Unbalanced Optimal Transport: Translation Invariant Sinkhorn and 1-D Frank-Wolfe](https://proceedings.mlr.press/v151/sejourne22a.html). In International Conference on Artificial Intelligence and Statistics (pp. 4995-5021). PMLR.
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[74] Tanguy, Eloi and Delon, Julie and Gozlan, Nathaël (2024). [Computing
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Barycentres of Measures for Generic Transport
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Costs](https://arxiv.org/abs/2501.04016). arXiv preprint 2501.04016 (2024)

RELEASES.md

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- Implement CG solvers for partial FGW (PR #687)
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- Added feature `grad=last_step` for `ot.solvers.solve` (PR #693)
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- Automatic PR labeling and release file update check (PR #704)
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- Implement fixed-point solver for OT barycenters with generic cost functions
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(generalizes `ot.lp.free_support_barycenter`). (PR #714)
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- Moved functions from `ot/lp/__init__.py` to separate modules. (PR #714)
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#### Closed issues
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- Fixed `ot.mapping` solvers which depended on deprecated `cvxpy` `ECOS` solver (PR #692, Issue #668)

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