Alternatives and similar repositories for COOT

Users that are interested in COOT are comparing it to the libraries listed below

• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆42Updated 5 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• ratschlab / SVGP-VAE
  Tensorflow implementation for the SVGP-VAE model.
  ☆22Updated 4 years ago
• trneedham / Spectral-Gromov-Wasserstein
  Graph matching and clustering by comparing heat kernels via optimal transport.
  ☆27Updated 2 years ago
• kasparmartens / NeuralDecomposition
  PyTorch implementation of the paper "Neural Decomposition: Functional ANOVA with Variational Autoencoders"
  ☆25Updated 5 years ago
• twistedcubic / copt
  [NeurIPS 2020]. COPT - Coordinated Optimal Transport on Graphs
  ☆16Updated 4 years ago
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• samirchowdhury / HyperCOT
  Code for computing Hypergraph Co-Optimal Transport distances
  ☆16Updated 2 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• KrishnaswamyLab / DiffusionEMD
  Code corresponding to the paper Diffusion Earth Mover's Distance and Distribution Embeddings
  ☆38Updated 11 months ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 5 years ago
• justkolesov / Wasserstein1Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).
  ☆21Updated last year
• iamalexkorotin / Wasserstein2Barycenters
  PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)
  ☆24Updated 3 years ago
• geomstats / challenge-iclr-2021
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆52Updated 3 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated 2 years ago
• cscarv / riemannian-metric-learning-ot
  ☆17Updated 2 years ago
• aripakman / neural_clustering_process
  Implementation of the Neural Clustering Process algorithm in Pytorch
  ☆31Updated 5 years ago
• rajesh-lab / deep_permutation_invariant
  Code accompanying paper "Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets."
  ☆29Updated 3 years ago
• iamalexkorotin / Wasserstein2Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)
  ☆45Updated 3 years ago
• chingyaoc / kV-Margin
  NeurIPS 2021, Code for Measuring Generalization with Optimal Transport
  ☆28Updated 4 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago
• dmilios / dirichletGPC
  ☆17Updated 6 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• hchau630 / LSC
  Code for "Disentangling images with Lie group transformations and sparse coding" (2023).
  ☆13Updated 4 years ago
• BorgwardtLab / topological-autoencoders
  Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
  ☆151Updated 3 years ago
• fedelopez77 / sympa
  Embedding graphs in symmetric spaces
  ☆30Updated 4 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago
• spbu-math-cs / Graph-Gaussian-Processes
  Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
  ☆53Updated 9 months ago
• iamalexkorotin / Wasserstein2GenerativeNetworks
  PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)
  ☆57Updated 2 years ago
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆102Updated 2 years ago