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RELEASES.md

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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`), with example. (PR #715)
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- Implement fixed-point solver for barycenters between GMMs (PR #715), with example.
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- Fix documentation in the module `ot.gaussian` (PR #718)
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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)

ot/gaussian.py

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@@ -354,7 +354,7 @@ def bures_wasserstein_barycenter(
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The function estimates the optimal barycenter of the
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empirical distributions. This is equivalent to resolving the fixed point
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algorithm for multiple Gaussian distributions :math:`\left{\mathcal{N}(\mu,\Sigma)\right}_{i=1}^n`
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algorithm for multiple Gaussian distributions :math:`\left\{\mathcal{N}(\mu,\Sigma)\right\}_{i=1}^n`
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:ref:`[1] <references-OT-mapping-linear-barycenter>`.
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The barycenter still following a Gaussian distribution :math:`\mathcal{N}(\mu_b,\Sigma_b)`
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The function estimates the optimal barycenter of the
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empirical distributions. This is equivalent to resolving the fixed point
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algorithm for multiple Gaussian distributions :math:`\left{\mathcal{N}(\mu,\Sigma)\right}_{i=1}^n`
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algorithm for multiple Gaussian distributions :math:`\left\{\mathcal{N}(\mu,\Sigma)\right\}_{i=1}^n`
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:ref:`[1] <references-OT-mapping-linear-barycenter>`.
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The barycenter still following a Gaussian distribution :math:`\mathcal{N}(\mu_b,\Sigma_b)`

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