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Title: Optimal Transport solvers comparison — POT Python Optimal Transport 0.9.6 documentation

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POT Python Optimal Transport https://pythonot.github.io/index.html
POT: Python Optimal Transporthttps://pythonot.github.io/index.html
Quickstart Guidehttps://pythonot.github.io/auto_examples/plot_quickstart_guide.html
Examples galleryhttps://pythonot.github.io/auto_examples/index.html
OT and regularized OThttps://pythonot.github.io/auto_examples/index.html#ot-and-regularized-ot
Introduction to Optimal Transport with Pythonhttps://pythonot.github.io/auto_examples/plot_Intro_OT.html
Optimal Transport for fixed supporthttps://pythonot.github.io/auto_examples/plot_OT_1D.html
Optimal Transport between empirical distributionshttps://pythonot.github.io/auto_examples/plot_OT_2D_samples.html
Optimal Transport with different ground metricshttps://pythonot.github.io/auto_examples/plot_OT_L1_vs_L2.html
Geometry of OT distanceshttps://pythonot.github.io/auto_examples/plot_compute_emd.html
Regularized OT with generic solverhttps://pythonot.github.io/auto_examples/plot_optim_OTreg.html
Quickstart Guidehttps://pythonot.github.io/auto_examples/plot_quickstart_guide.html
Optimal Transport solvers comparisonhttps://pythonot.github.io/auto_examples/plot_solve_variants.html
Generate datahttps://pythonot.github.io/auto_examples/plot_solve_variants.html#generate-data
Plot distributions and loss matrixhttps://pythonot.github.io/auto_examples/plot_solve_variants.html#plot-distributions-and-loss-matrix
Define Group lasso regularization and gradienthttps://pythonot.github.io/auto_examples/plot_solve_variants.html#define-group-lasso-regularization-and-gradient
Set up parameters for solvers and solvehttps://pythonot.github.io/auto_examples/plot_solve_variants.html#set-up-parameters-for-solvers-and-solve
Plot planshttps://pythonot.github.io/auto_examples/plot_solve_variants.html#plot-plans
Differentiable OT with PyTorchhttps://pythonot.github.io/auto_examples/index.html#differentiable-ot-with-pytorch
Gromov-Wasserstein (GW) and Fused GWhttps://pythonot.github.io/auto_examples/index.html#gromov-wasserstein-gw-and-fused-gw
Unbalanced and Partial OThttps://pythonot.github.io/auto_examples/index.html#unbalanced-and-partial-ot
OT in 1D and Sliced Wassersteinhttps://pythonot.github.io/auto_examples/index.html#ot-in-1d-and-sliced-wasserstein
OT on Gaussian and Gaussian Mixture Modelshttps://pythonot.github.io/auto_examples/index.html#ot-on-gaussian-and-gaussian-mixture-models
Factored an Low-Rank OThttps://pythonot.github.io/auto_examples/index.html#factored-an-low-rank-ot
Wasserstein and (F)GW barycentershttps://pythonot.github.io/auto_examples/index.html#wasserstein-and-f-gw-barycenters
Domain adaptation with OThttps://pythonot.github.io/auto_examples/index.html#domain-adaptation-with-ot
Other OT problemshttps://pythonot.github.io/auto_examples/index.html#other-ot-problems
User guidehttps://pythonot.github.io/user_guide.html
API and moduleshttps://pythonot.github.io/all.html
Releaseshttps://pythonot.github.io/releases.html
Contributorshttps://pythonot.github.io/contributors.html
Contributing to POThttps://pythonot.github.io/contributing.html
Code of conducthttps://pythonot.github.io/code_of_conduct.html
POT Python Optimal Transporthttps://pythonot.github.io/index.html
https://pythonot.github.io/index.html
Examples galleryhttps://pythonot.github.io/auto_examples/index.html
View page sourcehttps://pythonot.github.io/_sources/auto_examples/plot_solve_variants.rst.txt
Go to the endhttps://pythonot.github.io/auto_examples/plot_solve_variants.html#sphx-glr-download-auto-examples-plot-solve-variants-py
https://pythonot.github.io/auto_examples/plot_solve_variants.html#optimal-transport-solvers-comparison
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lst_regshttps://docs.python.org/3/library/stdtypes.html#list
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Download Jupyter notebook: plot_solve_variants.ipynbhttps://pythonot.github.io/_downloads/8ef8fd4d251060babb7f94a1610a6880/plot_solve_variants.ipynb
Download Python source code: plot_solve_variants.pyhttps://pythonot.github.io/_downloads/e0aaac1e7374a0c77ff58b5403e88b4e/plot_solve_variants.py
Download zipped: plot_solve_variants.ziphttps://pythonot.github.io/_downloads/766666d15248defb8aa962690e1bd50c/plot_solve_variants.zip
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