@@ -475,3 +475,44 @@ See also: [`barycenter`](@ref)
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function barycenter_unbalanced (A, C, ε, λ; kwargs... )
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return pot. barycenter_unbalanced (A, C, ε, λ; kwargs... )
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end
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+
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+ """
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+ gromov_wasserstein(μ, ν, Cμ, Cν, loss = "square_loss"; kwargs...)
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+
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+ Compute the exact Gromov-Wasserstein transport plan between `(μ, Cμ)` and `(ν, Cν)`.
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+
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+ The Gromov-Wasserstein transport problem seeks to find a minimizer of
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+ ```math
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+ \\ inf_{\\ gamma \\ in \\ Pi(\\ mu, \\ nu)} \\ sum_{i, j, k, l} L((C_μ)_{ik}, (C_ν)_{jl}) \\ gamma_{ij} \\ gamma_{kl},
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+ ```
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+ where ``L`` is quadratic (`loss = "square_loss"`) or the Kullback-Leibler divergence (`loss = "kl_loss"`).
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+
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+ This function is a wrapper of the function
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+ [`gromov_wasserstein`](https://pythonot.github.io/gen_modules/ot.gromov.html#ot.gromov.gromov_wasserstein) in the
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+ Python Optimal Transport package. Keyword arguments are listed in the documentation of the
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+ Python function.
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+ """
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+ function gromov_wasserstein (μ, ν, Cμ, Cν, loss= " square_loss" ; kwargs... )
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+ return pot. gromov. gromov_wasserstein (Cμ, Cν, μ, ν, loss; kwargs... )
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+ end
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+
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+ """
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+ entropic_gromov_wasserstein(μ, ν, Cμ, Cν, ε, loss = "square_loss"; kwargs...)
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+
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+ Compute the entropy-regularized Gromov-Wasserstein transport plan between `(μ, Cμ)` and `(ν, Cν)` with parameter `ε`.
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+
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+ The entropy-regularized Gromov-Wasserstein transport problem seeks to find a minimizer of
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+ ```math
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+ \\ 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),
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+ ```
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+ where ``L`` is quadratic (`loss = "square_loss"`) or the Kullback-Leibler divergence (`loss = "kl_loss"`)
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+ and ``\\ Omega(\\ gamma) = \\ sum_{ij} \\ gamma_{ij} \\ log(\\ gamma_{ij})`` is the entropic regularization term.
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+
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+ This function is a wrapper of the function
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+ [`entropic_gromov_wasserstein`](https://pythonot.github.io/gen_modules/ot.gromov.html#ot.gromov.entropic_gromov_wasserstein) in the
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+ Python Optimal Transport package. Keyword arguments are listed in the documentation of the
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+ Python function.
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+ """
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+ function entropic_gromov_wasserstein (μ, ν, Cμ, Cν, ε, loss= " square_loss" ; kwargs... )
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+ return pot. gromov. entropic_gromov_wasserstein (Cμ, Cν, μ, ν, loss, ε; kwargs... )
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+ end
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