Alternatives and similar repositories for FGW

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

• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆72Updated 5 years ago
• HongtengXu / s-gwl
  Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
  ☆44Updated 5 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 4 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆68Updated 5 years ago
• trneedham / gromov-wasserstein-statistics
  Statistics on the space of asymmetric networks via Gromov-Wasserstein distance
  ☆13Updated 5 years ago
• HongtengXu / Relational-Factorization-Model
  Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)
  ☆31Updated 2 years ago
• lchapel / partial-GW-for-PU
  Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…
  ☆21Updated 5 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• Hermina / GOT
  Code accompanying the NeurIPS 2019 paper "GOT: An Optimal Transport framework for Graph comparison"
  ☆41Updated last year
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆57Updated 6 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆83Updated 11 months ago
• jliu / graph-normalizing-flows
  Code for Graph Normalizing Flows.
  ☆63Updated 5 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆126Updated last year
• BorgwardtLab / TOGL
  Topological Graph Neural Networks (ICLR 2022)
  ☆124Updated 3 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆36Updated 5 years ago
• Haggaim / InvariantGraphNetworks
  Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"
  ☆24Updated 5 years ago
• BorgwardtLab / topological-autoencoders
  Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
  ☆150Updated 3 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• F-Bekerman / Graph-VAE
  ☆44Updated 7 years ago
• ermongroup / GraphScoreMatching
  Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling
  ☆111Updated 2 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆62Updated 4 years ago
• FabianFalck / mfcvae
  Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of var…
  ☆40Updated last year
• trneedham / Spectral-Gromov-Wasserstein
  Graph matching and clustering by comparing heat kernels via optimal transport.
  ☆26Updated 2 years ago
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• sigvae / SIGraphVAE
  ☆25Updated 5 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago