@@ -475,3 +475,44 @@ See also: [`barycenter`](@ref)
475475function barycenter_unbalanced (A, C, ε, λ; kwargs... )
476476 return pot. barycenter_unbalanced (A, C, ε, λ; kwargs... )
477477end
478+
479+ """
480+ gromov_wasserstein(μ, ν, Cμ, Cν, loss = "square_loss"; kwargs...)
481+
482+ Compute the exact Gromov-Wasserstein transport plan between `(μ, Cμ)` and `(ν, Cν)`.
483+
484+ The Gromov-Wasserstein transport problem seeks to find a minimizer of
485+ ```math
486+ \\ inf_{\\ gamma \\ in \\ Pi(\\ mu, \\ nu)} \\ sum_{i, j, k, l} L((C_μ)_{ik}, (C_ν)_{jl}) \\ gamma_{ij} \\ gamma_{kl},
487+ ```
488+ where ``L`` is quadratic (`loss = "square_loss"`) or the Kullback-Leibler divergence (`loss = "kl_loss"`).
489+
490+ This function is a wrapper of the function
491+ [`gromov_wasserstein`](https://pythonot.github.io/gen_modules/ot.gromov.html#ot.gromov.gromov_wasserstein) in the
492+ Python Optimal Transport package. Keyword arguments are listed in the documentation of the
493+ Python function.
494+ """
495+ function gromov_wasserstein (μ, ν, Cμ, Cν, loss= " square_loss" ; kwargs... )
496+ return pot. gromov. gromov_wasserstein (Cμ, Cν, μ, ν, loss; kwargs... )
497+ end
498+
499+ """
500+ entropic_gromov_wasserstein(μ, ν, Cμ, Cν, ε, loss = "square_loss"; kwargs...)
501+
502+ Compute the entropy-regularized Gromov-Wasserstein transport plan between `(μ, Cμ)` and `(ν, Cν)` with parameter `ε`.
503+
504+ The entropy-regularized Gromov-Wasserstein transport problem seeks to find a minimizer of
505+ ```math
506+ \\ inf_{\\ gamma \\ in \\ Pi(\\ mu, \\ nu)} \\ sum_{i, j, k, l} L((C_μ)_{ik}, (C_ν)_{jl}) \\ gamma_{ij} \\ gamma_{kl} + ε \\ Omega(\\ gamma),
507+ ```
508+ where ``L`` is quadratic (`loss = "square_loss"`) or the Kullback-Leibler divergence (`loss = "kl_loss"`)
509+ and ``\\ Omega(\\ gamma) = \\ sum_{ij} \\ gamma_{ij} \\ log(\\ gamma_{ij})`` is the entropic regularization term.
510+
511+ This function is a wrapper of the function
512+ [`entropic_gromov_wasserstein`](https://pythonot.github.io/gen_modules/ot.gromov.html#ot.gromov.entropic_gromov_wasserstein) in the
513+ Python Optimal Transport package. Keyword arguments are listed in the documentation of the
514+ Python function.
515+ """
516+ function entropic_gromov_wasserstein (μ, ν, Cμ, Cν, ε, loss= " square_loss" ; kwargs... )
517+ return pot. gromov. entropic_gromov_wasserstein (Cμ, Cν, μ, ν, loss, ε; kwargs... )
518+ end
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