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<section id="computation-times">
<span id="sphx-glr-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading"></a></h1>
<p><strong>18:25.779</strong> total execution time for 74 files <strong>from all galleries</strong>:</p>
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<tr class="row-odd"><th class="head"><p>Example</p></th>
<th class="head"><p>Time</p></th>
<th class="head"><p>Mem (MB)</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gromov/plot_gnn_TFGW.html#sphx-glr-auto-examples-gromov-plot-gnn-tfgw-py"><span class="std std-ref">Graph classification with Template Based Fused Gromov Wasserstein</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_gnn_TFGW.py</span></code>)</p></td>
<td><p>02:11.881</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/backends/plot_wass2_gan_torch.html#sphx-glr-auto-examples-backends-plot-wass2-gan-torch-py"><span class="std std-ref">Wasserstein 2 Minibatch GAN with PyTorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_wass2_gan_torch.py</span></code>)</p></td>
<td><p>01:59.546</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/backends/plot_Sinkhorn_gradients.html#sphx-glr-auto-examples-backends-plot-sinkhorn-gradients-py"><span class="std std-ref">Different gradient computations for regularized optimal transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_Sinkhorn_gradients.py</span></code>)</p></td>
<td><p>01:43.524</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/backends/plot_stoch_continuous_ot_pytorch.html#sphx-glr-auto-examples-backends-plot-stoch-continuous-ot-pytorch-py"><span class="std std-ref">Continuous OT plan estimation with Pytorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_stoch_continuous_ot_pytorch.py</span></code>)</p></td>
<td><p>01:05.241</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_generalized_free_support_barycenter.html#sphx-glr-auto-examples-barycenters-plot-generalized-free-support-barycenter-py"><span class="std std-ref">Generalized Wasserstein Barycenter Demo</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_generalized_free_support_barycenter.py</span></code>)</p></td>
<td><p>00:58.887</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/others/plot_SSNB.html#sphx-glr-auto-examples-others-plot-ssnb-py"><span class="std std-ref">Smooth and Strongly Convex Nearest Brenier Potentials</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_SSNB.py</span></code>)</p></td>
<td><p>00:57.478</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/sliced-wasserstein/plot_variance_ssw.html#sphx-glr-auto-examples-sliced-wasserstein-plot-variance-ssw-py"><span class="std std-ref">Spherical Sliced Wasserstein on distributions in S^2</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/sliced-wasserstein/plot_variance_ssw.py</span></code>)</p></td>
<td><p>00:56.334</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/backends/plot_sliced_wass_grad_flow_pytorch.html#sphx-glr-auto-examples-backends-plot-sliced-wass-grad-flow-pytorch-py"><span class="std std-ref">Sliced Wasserstein barycenter and gradient flow with PyTorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_sliced_wass_grad_flow_pytorch.py</span></code>)</p></td>
<td><p>00:42.556</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_color_images.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-color-images-py"><span class="std std-ref">OT for image color adaptation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_color_images.py</span></code>)</p></td>
<td><p>00:38.872</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/backends/plot_ssw_unif_torch.html#sphx-glr-auto-examples-backends-plot-ssw-unif-torch-py"><span class="std std-ref">Spherical Sliced-Wasserstein Embedding on Sphere</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_ssw_unif_torch.py</span></code>)</p></td>
<td><p>00:37.173</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/others/plot_dmmot.html#sphx-glr-auto-examples-others-plot-dmmot-py"><span class="std std-ref">Computing 1-dimensional Barycenters via d-MMOT</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_dmmot.py</span></code>)</p></td>
<td><p>00:35.601</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_regpath.html#sphx-glr-auto-examples-unbalanced-partial-plot-regpath-py"><span class="std std-ref">Regularization path of l2-penalized unbalanced optimal transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_regpath.py</span></code>)</p></td>
<td><p>00:34.938</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_mapping_colors_images.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-mapping-colors-images-py"><span class="std std-ref">OT for image color adaptation with mapping estimation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_mapping_colors_images.py</span></code>)</p></td>
<td><p>00:33.391</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_debiased_barycenter.html#sphx-glr-auto-examples-barycenters-plot-debiased-barycenter-py"><span class="std std-ref">Debiased Sinkhorn barycenter demo</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_debiased_barycenter.py</span></code>)</p></td>
<td><p>00:32.693</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gromov/plot_gromov_wasserstein_dictionary_learning.html#sphx-glr-auto-examples-gromov-plot-gromov-wasserstein-dictionary-learning-py"><span class="std std-ref">(Fused) Gromov-Wasserstein Linear Dictionary Learning</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_gromov_wasserstein_dictionary_learning.py</span></code>)</p></td>
<td><p>00:22.802</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_quickstart_guide.html#sphx-glr-auto-examples-plot-quickstart-guide-py"><span class="std std-ref">Quickstart Guide</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_quickstart_guide.py</span></code>)</p></td>
<td><p>00:21.660</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_convolutional_barycenter.html#sphx-glr-auto-examples-barycenters-plot-convolutional-barycenter-py"><span class="std std-ref">Convolutional Wasserstein Barycenter example</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_convolutional_barycenter.py</span></code>)</p></td>
<td><p>00:20.537</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/lowrank/plot_lowrank_sinkhorn.html#sphx-glr-auto-examples-lowrank-plot-lowrank-sinkhorn-py"><span class="std std-ref">Low rank Sinkhorn</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/lowrank/plot_lowrank_sinkhorn.py</span></code>)</p></td>
<td><p>00:19.648</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/backends/plot_dual_ot_pytorch.html#sphx-glr-auto-examples-backends-plot-dual-ot-pytorch-py"><span class="std std-ref">Dual OT solvers for entropic and quadratic regularized OT with Pytorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_dual_ot_pytorch.py</span></code>)</p></td>
<td><p>00:14.855</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_d2.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-d2-py"><span class="std std-ref">OT for domain adaptation on empirical distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_d2.py</span></code>)</p></td>
<td><p>00:08.930</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/others/plot_WDA.html#sphx-glr-auto-examples-others-plot-wda-py"><span class="std std-ref">Wasserstein Discriminant Analysis</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_WDA.py</span></code>)</p></td>
<td><p>00:07.810</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_quantized_gromov_wasserstein.html#sphx-glr-auto-examples-gromov-plot-quantized-gromov-wasserstein-py"><span class="std std-ref">Quantized Fused Gromov-Wasserstein examples</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_quantized_gromov_wasserstein.py</span></code>)</p></td>
<td><p>00:07.579</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gromov/plot_partial_fgw.html#sphx-glr-auto-examples-gromov-plot-partial-fgw-py"><span class="std std-ref">Plot partial FGW for subgraph matching</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_partial_fgw.py</span></code>)</p></td>
<td><p>00:07.550</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/others/plot_stochastic.html#sphx-glr-auto-examples-others-plot-stochastic-py"><span class="std std-ref">Stochastic examples</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_stochastic.py</span></code>)</p></td>
<td><p>00:07.197</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gromov/plot_gromov.html#sphx-glr-auto-examples-gromov-plot-gromov-py"><span class="std std-ref">Gromov-Wasserstein example</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_gromov.py</span></code>)</p></td>
<td><p>00:06.653</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/backends/plot_optim_gromov_pytorch.html#sphx-glr-auto-examples-backends-plot-optim-gromov-pytorch-py"><span class="std std-ref">Optimizing the Gromov-Wasserstein distance with PyTorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_optim_gromov_pytorch.py</span></code>)</p></td>
<td><p>00:06.275</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_solve_variants.html#sphx-glr-auto-examples-plot-solve-variants-py"><span class="std std-ref">Optimal Transport solvers comparison</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_solve_variants.py</span></code>)</p></td>
<td><p>00:05.673</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_semirelaxed_gromov_wasserstein_barycenter.html#sphx-glr-auto-examples-gromov-plot-semirelaxed-gromov-wasserstein-barycenter-py"><span class="std std-ref">Semi-relaxed (Fused) Gromov-Wasserstein Barycenter as Dictionary Learning</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_semirelaxed_gromov_wasserstein_barycenter.py</span></code>)</p></td>
<td><p>00:05.386</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/others/plot_outlier_detection_with_COOT_and_unbalanced_COOT.html#sphx-glr-auto-examples-others-plot-outlier-detection-with-coot-and-unbalanced-coot-py"><span class="std std-ref">Detecting outliers by learning sample marginal distribution with CO-Optimal Transport and by using unbalanced Co-Optimal Transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_outlier_detection_with_COOT_and_unbalanced_COOT.py</span></code>)</p></td>
<td><p>00:05.245</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_free_support_sinkhorn_barycenter.html#sphx-glr-auto-examples-barycenters-plot-free-support-sinkhorn-barycenter-py"><span class="std std-ref">2D free support Sinkhorn barycenters of distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_free_support_sinkhorn_barycenter.py</span></code>)</p></td>
<td><p>00:05.221</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_free_support_barycenter_generic_cost.html#sphx-glr-auto-examples-barycenters-plot-free-support-barycenter-generic-cost-py"><span class="std std-ref">OT Barycenter with Generic Costs Demo</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_free_support_barycenter_generic_cost.py</span></code>)</p></td>
<td><p>00:05.196</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_entropic_semirelaxed_fgw.html#sphx-glr-auto-examples-gromov-plot-entropic-semirelaxed-fgw-py"><span class="std std-ref">Entropic-regularized semi-relaxed (Fused) Gromov-Wasserstein example</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_entropic_semirelaxed_fgw.py</span></code>)</p></td>
<td><p>00:04.461</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/backends/plot_wass1d_torch.html#sphx-glr-auto-examples-backends-plot-wass1d-torch-py"><span class="std std-ref">Wasserstein 1D (flow and barycenter) with PyTorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_wass1d_torch.py</span></code>)</p></td>
<td><p>00:04.174</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_fgw_solvers.html#sphx-glr-auto-examples-gromov-plot-fgw-solvers-py"><span class="std std-ref">Comparison of Fused Gromov-Wasserstein solvers</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_fgw_solvers.py</span></code>)</p></td>
<td><p>00:03.795</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/sliced-wasserstein/plot_compute_wasserstein_circle.html#sphx-glr-auto-examples-sliced-wasserstein-plot-compute-wasserstein-circle-py"><span class="std std-ref">OT distance on the Circle</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/sliced-wasserstein/plot_compute_wasserstein_circle.py</span></code>)</p></td>
<td><p>00:03.769</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_unbalanced_OT.html#sphx-glr-auto-examples-unbalanced-partial-plot-unbalanced-ot-py"><span class="std std-ref">2D examples of exact and entropic unbalanced optimal transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_unbalanced_OT.py</span></code>)</p></td>
<td><p>00:03.753</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/others/plot_WeakOT_VS_OT.html#sphx-glr-auto-examples-others-plot-weakot-vs-ot-py"><span class="std std-ref">Weak Optimal Transport VS exact Optimal Transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_WeakOT_VS_OT.py</span></code>)</p></td>
<td><p>00:03.515</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_jcpot.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-jcpot-py"><span class="std std-ref">OT for multi-source target shift</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_jcpot.py</span></code>)</p></td>
<td><p>00:03.377</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_OT_2D_samples.html#sphx-glr-auto-examples-plot-ot-2d-samples-py"><span class="std std-ref">Optimal Transport between empirical distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_OT_2D_samples.py</span></code>)</p></td>
<td><p>00:03.180</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_Intro_OT.html#sphx-glr-auto-examples-plot-intro-ot-py"><span class="std std-ref">Introduction to Optimal Transport with Python</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_Intro_OT.py</span></code>)</p></td>
<td><p>00:03.010</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_laplacian.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-laplacian-py"><span class="std std-ref">OT with Laplacian regularization for domain adaptation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_laplacian.py</span></code>)</p></td>
<td><p>00:02.619</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/lowrank/plot_nystroem_approximation.html#sphx-glr-auto-examples-lowrank-plot-nystroem-approximation-py"><span class="std std-ref">Nyström approximation for OT</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/lowrank/plot_nystroem_approximation.py</span></code>)</p></td>
<td><p>00:02.574</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/lowrank/plot_factored_coupling.html#sphx-glr-auto-examples-lowrank-plot-factored-coupling-py"><span class="std std-ref">Optimal transport with factored couplings</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/lowrank/plot_factored_coupling.py</span></code>)</p></td>
<td><p>00:02.435</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/sliced-wasserstein/plot_variance.html#sphx-glr-auto-examples-sliced-wasserstein-plot-variance-py"><span class="std std-ref">Sliced Wasserstein Distance on 2D distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/sliced-wasserstein/plot_variance.py</span></code>)</p></td>
<td><p>00:02.410</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/lowrank/plot_lowrank_GW.html#sphx-glr-auto-examples-lowrank-plot-lowrank-gw-py"><span class="std std-ref">Low rank Gromov-Wasterstein between samples</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/lowrank/plot_lowrank_GW.py</span></code>)</p></td>
<td><p>00:02.384</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_conv_sinkhorn_ti.html#sphx-glr-auto-examples-unbalanced-partial-plot-conv-sinkhorn-ti-py"><span class="std std-ref">Translation Invariant Sinkhorn for Unbalanced Optimal Transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_conv_sinkhorn_ti.py</span></code>)</p></td>
<td><p>00:02.284</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_linear_mapping.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-linear-mapping-py"><span class="std std-ref">Linear OT mapping estimation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_linear_mapping.py</span></code>)</p></td>
<td><p>00:02.175</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_partial_wass_and_gromov.html#sphx-glr-auto-examples-unbalanced-partial-plot-partial-wass-and-gromov-py"><span class="std std-ref">Partial Wasserstein and Gromov-Wasserstein example</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_partial_wass_and_gromov.py</span></code>)</p></td>
<td><p>00:02.104</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/backends/plot_unmix_optim_torch.html#sphx-glr-auto-examples-backends-plot-unmix-optim-torch-py"><span class="std std-ref">Wasserstein unmixing with PyTorch</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_unmix_optim_torch.py</span></code>)</p></td>
<td><p>00:01.950</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_gromov_barycenter.html#sphx-glr-auto-examples-gromov-plot-gromov-barycenter-py"><span class="std std-ref">Gromov-Wasserstein Barycenter example</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_gromov_barycenter.py</span></code>)</p></td>
<td><p>00:01.945</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gaussian_gmm/plot_GMM_flow.html#sphx-glr-auto-examples-gaussian-gmm-plot-gmm-flow-py"><span class="std std-ref">Gradient Flow for GMM-OT distance</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gaussian_gmm/plot_GMM_flow.py</span></code>)</p></td>
<td><p>00:01.933</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_semirelaxed_fgw.html#sphx-glr-auto-examples-gromov-plot-semirelaxed-fgw-py"><span class="std std-ref">Semi-relaxed (Fused) Gromov-Wasserstein example</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_semirelaxed_fgw.py</span></code>)</p></td>
<td><p>00:01.752</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_barycenter_lp_vs_entropic.html#sphx-glr-auto-examples-barycenters-plot-barycenter-lp-vs-entropic-py"><span class="std std-ref">1D Wasserstein barycenter: exact LP vs entropic regularization</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_barycenter_lp_vs_entropic.py</span></code>)</p></td>
<td><p>00:01.695</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_OT_1D.html#sphx-glr-auto-examples-plot-ot-1d-py"><span class="std std-ref">Optimal Transport for fixed support</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_OT_1D.py</span></code>)</p></td>
<td><p>00:01.685</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_OT_L1_vs_L2.html#sphx-glr-auto-examples-plot-ot-l1-vs-l2-py"><span class="std std-ref">Optimal Transport with different ground metrics</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_OT_L1_vs_L2.py</span></code>)</p></td>
<td><p>00:01.681</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/gromov/plot_barycenter_fgw.html#sphx-glr-auto-examples-gromov-plot-barycenter-fgw-py"><span class="std std-ref">Barycenter of labeled graphs with FGW</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_barycenter_fgw.py</span></code>)</p></td>
<td><p>00:01.615</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_classes.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-classes-py"><span class="std std-ref">OT for domain adaptation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_classes.py</span></code>)</p></td>
<td><p>00:01.551</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_semi_supervised.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-semi-supervised-py"><span class="std std-ref">OTDA unsupervised vs semi-supervised setting</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_semi_supervised.py</span></code>)</p></td>
<td><p>00:01.510</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_free_support_barycenter.html#sphx-glr-auto-examples-barycenters-plot-free-support-barycenter-py"><span class="std std-ref">2D free support Wasserstein barycenters of distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_free_support_barycenter.py</span></code>)</p></td>
<td><p>00:01.432</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_optim_OTreg.html#sphx-glr-auto-examples-plot-optim-otreg-py"><span class="std std-ref">Regularized OT with generic solver</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_optim_OTreg.py</span></code>)</p></td>
<td><p>00:01.320</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_UOT_barycenter_1D.html#sphx-glr-auto-examples-unbalanced-partial-plot-uot-barycenter-1d-py"><span class="std std-ref">1D Wasserstein barycenter demo for Unbalanced distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_UOT_barycenter_1D.py</span></code>)</p></td>
<td><p>00:01.258</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/domain-adaptation/plot_otda_mapping.html#sphx-glr-auto-examples-domain-adaptation-plot-otda-mapping-py"><span class="std std-ref">OT mapping estimation for domain adaptation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/domain-adaptation/plot_otda_mapping.py</span></code>)</p></td>
<td><p>00:00.853</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/backends/plot_ot_batch.html#sphx-glr-auto-examples-backends-plot-ot-batch-py"><span class="std std-ref">Solving Many Optimal Transport Problems in Parallel</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/backends/plot_ot_batch.py</span></code>)</p></td>
<td><p>00:00.818</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/plot_compute_emd.html#sphx-glr-auto-examples-plot-compute-emd-py"><span class="std std-ref">Geometry of OT distances</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/plot_compute_emd.py</span></code>)</p></td>
<td><p>00:00.778</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gromov/plot_fgw.html#sphx-glr-auto-examples-gromov-plot-fgw-py"><span class="std std-ref">Plot Fused-Gromov-Wasserstein</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gromov/plot_fgw.py</span></code>)</p></td>
<td><p>00:00.675</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_barycenter_1D.html#sphx-glr-auto-examples-barycenters-plot-barycenter-1d-py"><span class="std std-ref">1D Wasserstein barycenter demo</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_barycenter_1D.py</span></code>)</p></td>
<td><p>00:00.601</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/others/plot_EWCA.html#sphx-glr-auto-examples-others-plot-ewca-py"><span class="std std-ref">Entropic Wasserstein Component Analysis</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_EWCA.py</span></code>)</p></td>
<td><p>00:00.537</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/others/plot_COOT.html#sphx-glr-auto-examples-others-plot-coot-py"><span class="std std-ref">Row and column alignments with CO-Optimal Transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_COOT.py</span></code>)</p></td>
<td><p>00:00.426</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/gaussian_gmm/plot_GMMOT_plan.html#sphx-glr-auto-examples-gaussian-gmm-plot-gmmot-plan-py"><span class="std std-ref">OT between GMM : plan and maps in 1D</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/gaussian_gmm/plot_GMMOT_plan.py</span></code>)</p></td>
<td><p>00:00.391</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_gaussian_barycenter.html#sphx-glr-auto-examples-barycenters-plot-gaussian-barycenter-py"><span class="std std-ref">Gaussian Bures-Wasserstein barycenters</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_gaussian_barycenter.py</span></code>)</p></td>
<td><p>00:00.348</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_UOT_1D.html#sphx-glr-auto-examples-unbalanced-partial-plot-uot-1d-py"><span class="std std-ref">1D Unbalanced optimal transport</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_UOT_1D.py</span></code>)</p></td>
<td><p>00:00.283</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/unbalanced-partial/plot_partial_1d.html#sphx-glr-auto-examples-unbalanced-partial-plot-partial-1d-py"><span class="std std-ref">Partial Wasserstein in 1D</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/unbalanced-partial/plot_partial_1d.py</span></code>)</p></td>
<td><p>00:00.244</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/barycenters/plot_gmm_barycenter.html#sphx-glr-auto-examples-barycenters-plot-gmm-barycenter-py"><span class="std std-ref">Gaussian Mixture Model OT Barycenters</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/barycenters/plot_gmm_barycenter.py</span></code>)</p></td>
<td><p>00:00.095</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/others/plot_logo.html#sphx-glr-auto-examples-others-plot-logo-py"><span class="std std-ref">Logo of the POT toolbox</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/others/plot_logo.py</span></code>)</p></td>
<td><p>00:00.055</p></td>
<td><p>0.0</p></td>
</tr>
</tbody>
</table>
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<span class="fa fa-book"> Python Optimal Transport</span> 0.9.6
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