Alternatives and similar repositories for Spectral-Gromov-Wasserstein

Users that are interested in Spectral-Gromov-Wasserstein are comparing it to the libraries listed below

• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆37Updated 5 years ago
• HongtengXu / Relational-Factorization-Model
  Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)
  ☆31Updated 3 years ago
• PythonOT / COOT
  CO-Optimal Transport
  ☆42Updated 5 years ago
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• fedelopez77 / sympa
  Embedding graphs in symmetric spaces
  ☆30Updated 4 years ago
• HongtengXu / s-gwl
  Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
  ☆44Updated 6 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆104Updated 3 years ago
• nkeriven / random-graph-gnn
  ☆12Updated 4 years ago
• BorgwardtLab / JointMDS
  Official implementation of Joint Multidimensional Scaling
  ☆24Updated 2 years ago
• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆42Updated 5 years ago
• trneedham / gromov-wasserstein-statistics
  Statistics on the space of asymmetric networks via Gromov-Wasserstein distance
  ☆15Updated 5 years ago
• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆73Updated 6 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• BorgwardtLab / filtration_curves
  Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
  ☆18Updated 2 years ago
• MarcTLaw / UltrahyperbolicRepresentation
  Ultrahyperbolic Representation Learning
  ☆13Updated 5 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 5 years ago
• matthieuheitz / WassersteinDictionaryLearning
  Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…
  ☆20Updated 6 years ago
• uestc-lese / SPGRL
  ☆18Updated 3 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 6 years ago
• mdeff / pygsp_tutorial_graphsip
  Graph signal processing tutorial, presented at the GraphSiP summer school.
  ☆78Updated 7 years ago
• samihaija / isvd
  Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning
  ☆21Updated 4 years ago
• fedelopez77 / gyrospd
  GyroSPD: Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices
  ☆18Updated 4 years ago
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆37Updated 2 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆105Updated 4 years ago
• cvignac / SMP
  ☆30Updated 4 years ago
• ratschlab / SVGP-VAE
  Tensorflow implementation for the SVGP-VAE model.
  ☆22Updated 4 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• gasteigerjo / gtn
  Graph transport network (GTN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, an…
  ☆15Updated 2 years ago