Alternatives and similar repositories for Hyperbolic-Embedding:

Users that are interested in Hyperbolic-Embedding are comparing it to the libraries listed below

• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆21Updated 4 years ago
• ydtydr / HyperbolicTiling_Learning
  Official implementation (learning part) for paper: Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models
  ☆18Updated 6 months ago
• crisbodnar / dgm
  Deep Graph Mapper: Seeing Graphs through the Neural Lens
  ☆55Updated last year
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆54Updated 3 years ago
• rsonthal / TreeRep
  Learning Tree structures and Tree metrics
  ☆23Updated 5 months ago
• vermaMachineLearning / FGSD
  Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).
  ☆24Updated 4 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆53Updated 2 years ago
• nkeriven / random-graph-gnn
  ☆12Updated 3 years ago
• cshjin / gnn_in_neurips_2019
  A comprehensive collection of GNN works in NeurIPS 2019.
  ☆21Updated 5 years ago
• fedelopez77 / gyrospd
  GyroSPD: Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices
  ☆18Updated 3 years ago
• hhcho / hyplinear
  MATLAB implementation of linear support vector classification in hyperbolic space
  ☆20Updated 6 years ago
• trneedham / Spectral-Gromov-Wasserstein
  Graph matching and clustering by comparing heat kernels via optimal transport.
  ☆26Updated 2 years ago
• c-hofer / nips2017
  Deprecated repository for "Deep Learning with Topological Signatures"
  ☆36Updated 4 years ago
• graphreason / graphreason.github.io
  Learning and Reasoning with Graph-Structured Data (ICML 2019 Workshop)
  ☆26Updated 5 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆103Updated 5 years ago
• qiangsiwei / poincare_embedding
  Poincaré Embedding
  ☆40Updated 7 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆123Updated last year
• arbenson / ScHoLP-Tutorial
  Tutorial for the ScHoLP.jl library and reproducing results from the accompanying paper.
  ☆40Updated 5 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 4 years ago
• Cyanogenoid / perm-optim
  [ICLR 2019] Learning Representations of Sets through Optimized Permutations
  ☆36Updated 5 years ago
• jacobdeasy / geometric-js
  ☆16Updated 3 years ago
• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆72Updated 5 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆31Updated 4 years ago
• karl-zhao / benchmarking-gnns-pyg
  ☆30Updated last year
• PurdueMINDS / RelationalPooling
  ☆35Updated 5 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 5 years ago
• hichamjanati / mtw
  Wasserstein regularization for sparse multi-task regression
  ☆15Updated 4 years ago
• PurdueMINDS / JanossyPooling
  ☆26Updated 6 years ago
• nd7141 / AWE
  Compute graph embeddings via Anonymous Walk Embeddings
  ☆81Updated 6 years ago