searchindex.js

Search.setIndex({"alltitles": {"(Fused) Gromov-Wasserstein Linear Dictionary Learning": [[36, null]], "0.1.10": [[107, "id38"]], "0.1.11": [[107, "id37"]], "0.1.3": [[107, "id41"]], "0.1.7": [[107, "id40"]], "0.1.9": [[107, "id39"]], "0.3": [[107, "id36"]], "0.3.1": [[107, "id35"]], "0.4": [[107, "id32"]], "0.5.0": [[107, "id29"]], "0.6.0": [[107, "id26"]], "0.7.0": [[107, "id24"]], "0.8.0": [[107, "id21"]], "0.8.1": [[107, "id18"]], "0.8.1.0": [[107, "id16"]], "0.8.2": [[107, "id13"]], "0.9.1": [[107, "id10"]], "0.9.2": [[107, "id7"]], "0.9.3": [[107, "id5"]], "0.9.4": [[107, "id2"]], "0.9.5": [[107, "id1"]], "1D Unbalanced optimal transport": [[71, null]], "1D Wasserstein barycenter demo": [[10, null]], "1D Wasserstein barycenter demo for Unbalanced distributions": [[72, null]], "1D Wasserstein barycenter: exact LP vs entropic regularization": [[11, null]], "2D examples of exact and entropic unbalanced optimal transport": [[76, null]], "2D free support Sinkhorn barycenters of distributions": [[15, null]], "2D free support Wasserstein barycenters of distributions": [[14, null]], "API and modules": [[0, null]], "Acknowledgements": [[105, "acknowledgements"]], "Acknowledgments": [[80, "acknowledgments"]], "Add node features": [[30, "add-node-features"], [38, "add-node-features"]], "Algorithm": [[58, "algorithm"]], "An example of convolutional barycenter (ot.bregman.convolutional_barycenter2d) computation": [[106, "an-example-of-convolutional-barycenter-ot-bregman-convolutional-barycenter2d-computation"]], "Anaconda installation with conda-forge": [[105, "anaconda-installation-with-conda-forge"]], "Animate trajectories of generated samples along iteration": [[4, "animate-trajectories-of-generated-samples-along-iteration"], [8, "animate-trajectories-of-generated-samples-along-iteration"]], "Animate trajectories of the barycenter along gradient descent": [[3, "animate-trajectories-of-the-barycenter-along-gradient-descent"]], "Animate trajectories of the gradient flow along iteration": [[3, "animate-trajectories-of-the-gradient-flow-along-iteration"]], "Animation of the regpath for UOT l2": [[75, "animation-of-the-regpath-for-uot-l2"]], "Animation of the regpath for semi-relaxed UOT l2": [[75, "animation-of-the-regpath-for-semi-relaxed-uot-l2"]], "Attribution": [[78, "attribution"]], "Barycenter computation": [[10, "barycenter-computation"], [29, "barycenter-computation"], [35, "barycenter-computation"], [72, "barycenter-computation"]], "Barycenter computation and plot": [[17, "barycenter-computation-and-plot"]], "Barycenter computation and visualization": [[12, "barycenter-computation-and-visualization"], [13, "barycenter-computation-and-visualization"]], "Barycenters with fixed support": [[106, "barycenters-with-fixed-support"]], "Barycenters with free support": [[106, "barycenters-with-free-support"]], "Barycentric interpolation": [[10, "barycentric-interpolation"], [72, "barycentric-interpolation"]], "Breaking change": [[107, "breaking-change"]], "Classes": [[81, "classes"], [84, "classes"], [100, "classes"], [103, "classes"]], "Closed issues": [[107, "closed-issues"], [107, "id4"], [107, "id6"], [107, "id9"], [107, "id12"], [107, "id15"], [107, "id17"], [107, "id20"], [107, "id23"], [107, "id25"], [107, "id28"], [107, "id31"], [107, "id34"]], "Code of conduct": [[78, null]], "Community clustering with uniform and estimated weights": [[2, "community-clustering-with-uniform-and-estimated-weights"]], "Compare Barycenters in both methods": [[49, "compare-barycenters-in-both-methods"], [49, "id1"]], "Compare the Euclidean Wasserstein distance with the Wasserstein distance on the  circle": [[64, "compare-the-euclidean-wasserstein-distance-with-the-wasserstein-distance-on-the-circle"]], "Compare the results with the Sinkhorn algorithm": [[56, "compare-the-results-with-the-sinkhorn-algorithm"]], "Compare with original distributions": [[49, "compare-with-original-distributions"]], "Comparison of Fused Gromov-Wasserstein solvers": [[32, null]], "Computation times": [[9, null], [18, null], [28, null], [40, null], [57, null], [67, null], [70, null], [77, null], [108, null]], "Compute Bures-Wasserstein barycenters and plot them": [[16, "compute-bures-wasserstein-barycenters-and-plot-them"]], "Compute EMD": [[61, "compute-emd"]], "Compute EMD for the different losses": [[63, "compute-emd-for-the-different-losses"]], "Compute EWCA": [[43, "compute-ewca"]], "Compute FGW/GW": [[31, "compute-fgw-gw"]], "Compute Factored OT and exact OT solutions": [[50, "compute-factored-ot-and-exact-ot-solutions"]], "Compute Fisher Discriminant Analysis": [[47, "compute-fisher-discriminant-analysis"]], "Compute GW with scalable stochastic methods with any loss function": [[34, "compute-gw-with-scalable-stochastic-methods-with-any-loss-function"]], "Compute Gromov-Wasserstein plans and distance": [[34, "compute-gromov-wasserstein-plans-and-distance"]], "Compute Sinkhorn": [[61, "compute-sinkhorn"]], "Compute Sinkhorn for the different losses": [[63, "compute-sinkhorn-for-the-different-losses"]], "Compute Wasserstein Discriminant Analysis": [[47, "compute-wasserstein-discriminant-analysis"]], "Compute Weak OT and exact OT solutions": [[48, "compute-weak-ot-and-exact-ot-solutions"]], "Compute distance kernels, normalize them and then display": [[34, "compute-distance-kernels-normalize-them-and-then-display"]], "Compute entropic kl-regularized UOT with Sinkhorn and Translation Invariant Sinkhorn": [[73, "compute-entropic-kl-regularized-uot-with-sinkhorn-and-translation-invariant-sinkhorn"]], "Compute entropic kl-regularized UOT, kl- and l2-regularized UOT": [[76, "compute-entropic-kl-regularized-uot-kl-and-l2-regularized-uot"]], "Compute free support Wasserstein barycenter": [[14, "compute-free-support-wasserstein-barycenter"]], "Compute partial Gromov-Wasserstein plans and distance": [[74, "compute-partial-gromov-wasserstein-plans-and-distance"]], "Compute partial Wasserstein plans and distance": [[74, "compute-partial-wasserstein-plans-and-distance"]], "Compute semi-relaxed and fully relaxed regularization paths": [[75, "compute-semi-relaxed-and-fully-relaxed-regularization-paths"]], "Compute the Sliced Wasserstein Barycenter": [[3, "compute-the-sliced-wasserstein-barycenter"]], "Compute the Transportation Matrix for the Dual Problem": [[56, "compute-the-transportation-matrix-for-the-dual-problem"]], "Compute the Transportation Matrix for the Semi-Dual Problem": [[56, "compute-the-transportation-matrix-for-the-semi-dual-problem"]], "Compute the quantized Fused Gromov-Wasserstein distance between samples using the wrapper": [[37, "compute-the-quantized-fused-gromov-wasserstein-distance-between-samples-using-the-wrapper"]], "Compute the quantized Gromov-Wasserstein distance using the wrapper": [[37, "compute-the-quantized-gromov-wasserstein-distance-using-the-wrapper"]], "Compute their Fused Gromov-Wasserstein distances": [[32, "compute-their-fused-gromov-wasserstein-distances"]], "Compute their entropic-regularized semi-relaxed Gromov-Wasserstein divergences": [[30, "compute-their-entropic-regularized-semi-relaxed-gromov-wasserstein-divergences"]], "Compute their quantized Gromov-Wasserstein distance without using the wrapper": [[37, "compute-their-quantized-gromov-wasserstein-distance-without-using-the-wrapper"]], "Compute their semi-relaxed Fused Gromov-Wasserstein divergences": [[30, "compute-their-semi-relaxed-fused-gromov-wasserstein-divergences"], [38, "compute-their-semi-relaxed-fused-gromov-wasserstein-divergences"]], "Compute their semi-relaxed Gromov-Wasserstein divergences": [[38, "compute-their-semi-relaxed-gromov-wasserstein-divergences"]], "Computing Wasserstein distance": [[106, "computing-wasserstein-distance"]], "Computing d-dimensional Barycenters via d-MMOT": [[49, null]], "Contents": [[105, "contents"]], "Continuous OT plan estimation with Pytorch": [[5, null]], "Contributing to POT": [[79, null]], "Contributions and code of conduct": [[105, "contributions-and-code-of-conduct"]], "Contributors": [[80, null], [80, "contributors"]], "Convert data to torch tensors": [[1, "convert-data-to-torch-tensors"], [5, "convert-data-to-torch-tensors"]], "Convolutional Wasserstein Barycenter example": [[12, null]], "Cost matrix": [[58, "cost-matrix"]], "Create structure matrices and across-feature distance matrix": [[31, "create-structure-matrices-and-across-feature-distance-matrix"]], "Creators and Maintainers": [[80, "creators-and-maintainers"]], "Data for logo": [[51, "data-for-logo"]], "Data generation": [[1, "data-generation"], [4, "data-generation"], [5, "data-generation"], [8, "data-generation"]], "Data preparation": [[12, "data-preparation"], [35, "data-preparation"]], "Dataset 1 : Plot OT Matrices": [[62, "dataset-1-plot-ot-matrices"]], "Dataset 1 : uniform sampling": [[62, "dataset-1-uniform-sampling"]], "Dataset 2 : Partial circle": [[62, "dataset-2-partial-circle"]], "Dataset 2 : Plot  OT Matrices": [[62, "dataset-2-plot-ot-matrices"]], "Debiased Sinkhorn barycenter demo": [[13, null]], "Debiased barycenter of 1D Gaussians": [[13, "debiased-barycenter-of-1d-gaussians"]], "Debiased barycenter of 2D images": [[13, "debiased-barycenter-of-2d-images"]], "Define Gaussian Covariances and distributions": [[16, "define-gaussian-covariances-and-distributions"]], "Define Group lasso regularization and gradient": [[66, "define-group-lasso-regularization-and-gradient"]], "Dependencies": [[105, "dependencies"]], "Dependency": [[82, null]], "Deprecation": [[107, "deprecation"]], "Detecting outliers by learning sample marginal distribution with CO-Optimal Transport and by using unbalanced Co-Optimal Transport": [[54, null]], "Dirac Data": [[11, "dirac-data"]], "Discrete case": [[56, "discrete-case"]], "Documentation": [[79, "documentation"]], "Domain adaptation classes": [[106, "domain-adaptation-classes"]], "Domain adaptation examples": [[41, "domain-adaptation-examples"]], "Domain adaptation for pixel distribution transfer": [[26, "domain-adaptation-for-pixel-distribution-transfer"]], "Dual OT solvers for entropic and quadratic regularized OT with Pytorch": [[1, null]], "Empirical Sinkhorn": [[61, "empirical-sinkhorn"]], "Endow the dataset with node features": [[36, "endow-the-dataset-with-node-features"], [39, "endow-the-dataset-with-node-features"]], "Enforcement": [[78, "enforcement"]], "Entropic Gromov-Wasserstein": [[52, "entropic-gromov-wasserstein"]], "Entropic Wasserstein Component Analysis": [[43, null]], "Entropic regularized OT": [[106, "entropic-regularized-ot"]], "Entropic-regularized semi-relaxed (Fused) Gromov-Wasserstein example": [[30, null]], "Estimate a Fused Gromov-Wasserstein dictionary from the dataset of attributed graphs": [[36, "estimate-a-fused-gromov-wasserstein-dictionary-from-the-dataset-of-attributed-graphs"]], "Estimate linear mapping and transport": [[24, "estimate-linear-mapping-and-transport"]], "Estimate mapping and adapt": [[24, "estimate-mapping-and-adapt"]], "Estimate the Gromov-Wasserstein dictionary from the dataset": [[36, "estimate-the-gromov-wasserstein-dictionary-from-the-dataset"]], "Estimate the srFGW barycenter from the attributed graphs and visualize embeddings": [[39, "estimate-the-srfgw-barycenter-from-the-attributed-graphs-and-visualize-embeddings"]], "Estimate the srGW barycenter from the dataset and visualize embeddings": [[39, "estimate-the-srgw-barycenter-from-the-dataset-and-visualize-embeddings"]], "Estimated weights and convergence of the objective": [[6, "estimated-weights-and-convergence-of-the-objective"]], "Estimating deep dual variables for entropic OT": [[5, "estimating-deep-dual-variables-for-entropic-ot"]], "Estimating dual variables for entropic OT": [[1, "estimating-dual-variables-for-entropic-ot"]], "Estimating dual variables for quadratic OT": [[1, "estimating-dual-variables-for-quadratic-ot"]], "Examples": [[105, "examples"]], "Examples and Notebooks": [[105, "examples-and-notebooks"]], "Examples gallery": [[41, null]], "Examples of GW, regularized G and FGW barycenters": [[106, "examples-of-gw-regularized-g-and-fgw-barycenters"]], "Examples of Partial OT": [[106, "examples-of-partial-ot"]], "Examples of Unbalanced OT": [[106, "examples-of-unbalanced-ot"]], "Examples of Unbalanced OT barycenters": [[106, "examples-of-unbalanced-ot-barycenters"]], "Examples of Wasserstein and regularized Wasserstein barycenters": [[106, "examples-of-wasserstein-and-regularized-wasserstein-barycenters"]], "Examples of computation of GW, regularized G and FGW": [[106, "examples-of-computation-of-gw-regularized-g-and-fgw"]], "Examples of free support barycenter estimation": [[106, "examples-of-free-support-barycenter-estimation"]], "Examples of group Lasso regularization": [[106, "examples-of-group-lasso-regularization"]], "Examples of the generic solvers": [[106, "examples-of-the-generic-solvers"]], "Examples of the use of OTDA classes": [[106, "examples-of-the-use-of-otda-classes"]], "Examples of the use of WDA": [[106, "examples-of-the-use-of-wda"]], "Examples of use for ot.emd": [[106, "examples-of-use-for-ot-emd"]], "Examples of use for ot.emd2": [[106, "examples-of-use-for-ot-emd2"]], "Examples of use for ot.sinkhorn": [[106, "examples-of-use-for-ot-sinkhorn"]], "Examples of use for ot.sinkhorn2": [[106, "examples-of-use-for-ot-sinkhorn2"]], "Examples of use of quadratic regularization": [[106, "examples-of-use-of-quadratic-regularization"]], "Examples using ot.coot.co_optimal_transport": [[83, "examples-using-ot-coot-co-optimal-transport"]], "Examples using ot.coot.co_optimal_transport2": [[83, "examples-using-ot-coot-co-optimal-transport2"]], "Examples using ot.da.BaseTransport": [[84, "examples-using-ot-da-basetransport"]], "Examples using ot.da.EMDLaplaceTransport": [[84, "examples-using-ot-da-emdlaplacetransport"]], "Examples using ot.da.EMDTransport": [[84, "examples-using-ot-da-emdtransport"]], "Examples using ot.da.JCPOTTransport": [[84, "examples-using-ot-da-jcpottransport"]], "Examples using ot.da.LinearGWTransport": [[84, "examples-using-ot-da-lineargwtransport"]], "Examples using ot.da.LinearTransport": [[84, "examples-using-ot-da-lineartransport"]], "Examples using ot.da.MappingTransport": [[84, "examples-using-ot-da-mappingtransport"]], "Examples using ot.da.SinkhornL1l2Transport": [[84, "examples-using-ot-da-sinkhornl1l2transport"]], "Examples using ot.da.SinkhornLpl1Transport": [[84, "examples-using-ot-da-sinkhornlpl1transport"]], "Examples using ot.da.SinkhornTransport": [[84, "examples-using-ot-da-sinkhorntransport"]], "Examples using ot.datasets.make_1D_gauss": [[85, "examples-using-ot-datasets-make-1d-gauss"]], "Examples using ot.datasets.make_2D_samples_gauss": [[85, "examples-using-ot-datasets-make-2d-samples-gauss"]], "Examples using ot.datasets.make_data_classif": [[85, "examples-using-ot-datasets-make-data-classif"]], "Examples using ot.dr.ewca": [[86, "examples-using-ot-dr-ewca"]], "Examples using ot.dr.fda": [[86, "examples-using-ot-dr-fda"]], "Examples using ot.dr.wda": [[86, "examples-using-ot-dr-wda"]], "Examples using ot.gaussian.bures_wasserstein_barycenter": [[88, "examples-using-ot-gaussian-bures-wasserstein-barycenter"]], "Examples using ot.gaussian.empirical_bures_wasserstein_mapping": [[88, "examples-using-ot-gaussian-empirical-bures-wasserstein-mapping"]], "Examples using ot.gaussian.empirical_gaussian_gromov_wasserstein_mapping": [[88, "examples-using-ot-gaussian-empirical-gaussian-gromov-wasserstein-mapping"]], "Examples using ot.gmm.gmm_ot_apply_map": [[89, "examples-using-ot-gmm-gmm-ot-apply-map"]], "Examples using ot.gmm.gmm_ot_loss": [[89, "examples-using-ot-gmm-gmm-ot-loss"]], "Examples using ot.gmm.gmm_ot_plan_density": [[89, "examples-using-ot-gmm-gmm-ot-plan-density"]], "Examples using ot.gmm.gmm_pdf": [[89, "examples-using-ot-gmm-gmm-pdf"]], "Examples using ot.lp.free_support_barycenter": [[93, "examples-using-ot-lp-free-support-barycenter"]], "Examples using ot.lp.generalized_free_support_barycenter": [[93, "examples-using-ot-lp-generalized-free-support-barycenter"]], "Examples using ot.mapping.nearest_brenier_potential_fit": [[94, "examples-using-ot-mapping-nearest-brenier-potential-fit"]], "Examples using ot.mapping.nearest_brenier_potential_predict_bounds": [[94, "examples-using-ot-mapping-nearest-brenier-potential-predict-bounds"]], "Examples using ot.optim.cg": [[95, "examples-using-ot-optim-cg"]], "Examples using ot.optim.gcg": [[95, "examples-using-ot-optim-gcg"]], "Examples using ot.partial.entropic_partial_wasserstein": [[96, "examples-using-ot-partial-entropic-partial-wasserstein"]], "Examples using ot.partial.partial_wasserstein": [[96, "examples-using-ot-partial-partial-wasserstein"]], "Examples using ot.plot.plot1D_mat": [[97, "examples-using-ot-plot-plot1d-mat"]], "Examples using ot.plot.plot2D_samples_mat": [[97, "examples-using-ot-plot-plot2d-samples-mat"]], "Examples using ot.plot.rescale_for_imshow_plot": [[97, "examples-using-ot-plot-rescale-for-imshow-plot"]], "Examples using ot.regpath.compute_transport_plan": [[98, "examples-using-ot-regpath-compute-transport-plan"]], "Examples using ot.regpath.regularization_path": [[98, "examples-using-ot-regpath-regularization-path"]], "Examples using ot.smooth.smooth_ot_dual": [[100, "examples-using-ot-smooth-smooth-ot-dual"]], "Examples using ot.stochastic.loss_dual_entropic": [[101, "examples-using-ot-stochastic-loss-dual-entropic"]], "Examples using ot.stochastic.loss_dual_quadratic": [[101, "examples-using-ot-stochastic-loss-dual-quadratic"]], "Examples using ot.stochastic.plan_dual_entropic": [[101, "examples-using-ot-stochastic-plan-dual-entropic"]], "Examples using ot.stochastic.plan_dual_quadratic": [[101, "examples-using-ot-stochastic-plan-dual-quadratic"]], "Examples using ot.stochastic.solve_dual_entropic": [[101, "examples-using-ot-stochastic-solve-dual-entropic"]], "Examples using ot.stochastic.solve_semi_dual_entropic": [[101, "examples-using-ot-stochastic-solve-semi-dual-entropic"]], "Examples using ot.utils.BaseEstimator": [[103, "examples-using-ot-utils-baseestimator"]], "Examples using ot.utils.dist0": [[103, "examples-using-ot-utils-dist0"]], "Examples using ot.utils.proj_SDP": [[103, "examples-using-ot-utils-proj-sdp"]], "Examples using ot.utils.proj_simplex": [[103, "examples-using-ot-utils-proj-simplex"]], "Exceptions": [[103, "exceptions"]], "FAQ": [[106, "faq"]], "Features": [[107, "features"], [107, "id27"], [107, "id30"], [107, "id33"]], "Fig 1 : plots source and target samples": [[19, "fig-1-plots-source-and-target-samples"], [22, "fig-1-plots-source-and-target-samples"], [23, "fig-1-plots-source-and-target-samples"]], "Fig 1 : plots source and target samples + matrix of pairwise distance": [[21, "fig-1-plots-source-and-target-samples-matrix-of-pairwise-distance"], [27, "fig-1-plots-source-and-target-samples-matrix-of-pairwise-distance"]], "Fig 2 : plot optimal couplings and transported samples": [[19, "fig-2-plot-optimal-couplings-and-transported-samples"], [22, "fig-2-plot-optimal-couplings-and-transported-samples"], [23, "fig-2-plot-optimal-couplings-and-transported-samples"]], "Fig 2 : plots optimal couplings for the different methods": [[21, "fig-2-plots-optimal-couplings-for-the-different-methods"], [27, "fig-2-plots-optimal-couplings-for-the-different-methods"]], "Fig 3 : plot transported samples": [[21, "fig-3-plot-transported-samples"], [27, "fig-3-plot-transported-samples"]], "Filing bugs": [[79, "filing-bugs"]], "Final figure": [[11, "final-figure"]], "First OT Problem": [[58, "first-ot-problem"]], "First pre-release": [[107, "first-pre-release"]], "Functions": [[81, "functions"], [83, "functions"], [84, "functions"], [85, "functions"], [86, "functions"], [87, "functions"], [88, "functions"], [89, "functions"], [92, "functions"], [93, "functions"], [94, "functions"], [95, "functions"], [96, "functions"], [97, "functions"], [98, "functions"], [99, "functions"], [100, "functions"], [101, "functions"], [103, "functions"], [104, "functions"]], "GMM Flow": [[45, null]], "GMM Plan 1D": [[44, null]], "GPU acceleration": [[106, "gpu-acceleration"]], "Gaussian Bures-Wasserstein barycenters": [[16, null]], "Gaussian Data": [[11, "gaussian-data"]], "General Parameters": [[15, "general-parameters"]], "Generalized Wasserstein Barycenter Demo": [[17, null]], "Generate Data": [[15, "generate-data"]], "Generate GMMOT maps and plot them over plan": [[44, "generate-gmmot-maps-and-plot-them-over-plan"]], "Generate GMMOT plan plot it": [[44, "generate-gmmot-plan-plot-it"]], "Generate a dataset composed of graphs following Stochastic Block models of 1, 2 and 3 clusters.": [[36, "generate-a-dataset-composed-of-graphs-following-stochastic-block-models-of-1-2-and-3-clusters"], [39, "generate-a-dataset-composed-of-graphs-following-stochastic-block-models-of-1-2-and-3-clusters"]], "Generate and plot data": [[17, "generate-and-plot-data"]], "Generate and visualize data": [[8, "generate-and-visualize-data"]], "Generate attributed point clouds": [[37, "generate-attributed-point-clouds"]], "Generate data": [[6, "generate-data"], [10, "generate-data"], [14, "generate-data"], [19, "generate-data"], [20, "generate-data"], [21, "generate-data"], [22, "generate-data"], [23, "generate-data"], [24, "generate-data"], [25, "generate-data"], [26, "generate-data"], [27, "generate-data"], [29, "generate-data"], [31, "generate-data"], [33, "generate-data"], [43, "generate-data"], [47, "generate-data"], [52, "generate-data"], [53, "generate-data"], [54, "generate-data"], [55, "generate-data"], [59, "generate-data"], [60, "generate-data"], [61, "generate-data"], [63, "generate-data"], [65, "generate-data"], [66, "generate-data"], [68, "generate-data"], [69, "generate-data"], [71, "generate-data"], [72, "generate-data"], [75, "generate-data"], [76, "generate-data"]], "Generate data an plot it": [[48, "generate-data-an-plot-it"], [50, "generate-data-an-plot-it"]], "Generate data and plot it": [[45, "generate-data-and-plot-it"]], "Generate graphs": [[37, "generate-graphs"]], "Generate two graphs following Stochastic Block models of 2 and 3 clusters.": [[30, "generate-two-graphs-following-stochastic-block-models-of-2-and-3-clusters"], [32, "generate-two-graphs-following-stochastic-block-models-of-2-and-3-clusters"], [38, "generate-two-graphs-following-stochastic-block-models-of-2-and-3-clusters"]], "Generating 2 distributions": [[49, "generating-2-distributions"]], "Generator Model": [[8, "generator-model"]], "Generic solvers": [[106, "generic-solvers"]], "Getting help": [[58, "getting-help"]], "Gradient descent": [[4, "gradient-descent"]], "Gradient 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