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
  ☆37Updated 5 years ago
• nd7141 / AWE
  Compute graph embeddings via Anonymous Walk Embeddings
  ☆83Updated 7 years ago
• c-hofer / nips2017
  Deprecated repository for "Deep Learning with Topological Signatures"
  ☆36Updated 5 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 6 years ago
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆137Updated 6 years ago
• lateral / frechet-mean-hyperboloid
  ☆16Updated 7 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆59Updated 6 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆130Updated 2 years ago
• jacobdeasy / geometric-js
  ☆17Updated 4 years ago
• PurdueMINDS / Equivalence
  Equivalence Between Structural Representations and Positional Node Embeddings
  ☆22Updated 5 years ago
• vermaMachineLearning / FGSD
  Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).
  ☆24Updated 5 years ago
• drewwilimitis / hyperbolic-learning
  Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
  ☆144Updated 5 years ago
• giannisnik / cnn-graph-classification
  A convolutional neural network for graph classification in PyTorch
  ☆91Updated 6 years ago
• ferrine / hyrnn
  Hyperbolic Neural Networks, pytorch
  ☆87Updated 6 years ago
• guillaumejaume / edGNN
  Code for the paper: "edGNN: A simple and powerful GNN for labeled graphs"
  ☆43Updated 2 years ago
• benedekrozemberczki / GraphWaveMachine
  A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".
  ☆189Updated 2 years ago
• Hanjun-Dai / steady_state_embedding
  Learning Steady-States of Iterative Algorithms over Graphs
  ☆40Updated 7 years ago
• BorgwardtLab / P-WL
  A Persistent Weisfeiler–Lehman Procedure for Graph Classification
  ☆62Updated 4 years ago
• google / gumbel_sinkhorn
  ☆77Updated 8 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• mdeff / pygsp_tutorial_graphsip
  Graph signal processing tutorial, presented at the GraphSiP summer school.
  ☆78Updated 7 years ago
• crisbodnar / dgm
  Deep Graph Mapper: Seeing Graphs through the Neural Lens
  ☆58Updated 2 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆66Updated 5 years ago
• hhcho / hyplinear
  MATLAB implementation of linear support vector classification in hyperbolic space
  ☆21Updated 7 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆86Updated last year
• Cyanogenoid / perm-optim
  [ICLR 2019] Learning Representations of Sets through Optimized Permutations
  ☆36Updated 6 years ago
• nimadehmamy / Understanding-GCN
  code for the paper in NeurIPS 2019
  ☆40Updated 2 years ago
• Chen-Cai-OSU / LDP
  LDP for graph classification
  ☆23Updated 6 years ago
• arbenson / ScHoLP-Tutorial
  Tutorial for the ScHoLP.jl library and reproducing results from the accompanying paper.
  ☆43Updated 6 years ago
• qiangsiwei / poincare_embedding
  Poincaré Embedding
  ☆39Updated 8 years ago