Alternatives and similar repositories for HGCAE:

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

• JindouDai / H2H-GCN
  ☆14Updated 3 years ago
• jw9730 / hot
  [NeurIPS'21] Higher-order Transformers for sets, graphs, and hypergraphs, in PyTorch
  ☆62Updated 2 years ago
• MinaGhadimiAtigh / Hyperbolic-Busemann-Learning
  Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021
  ☆24Updated 3 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆54Updated 3 years ago
• chingyaoc / InfoOT
  [ICML2023] InfoOT: Information Maximizing Optimal Transport
  ☆40Updated last year
• harryjo97 / EHGNN
  Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)
  ☆52Updated last year
• ihollywhy / DistillGCN.PyTorch
  Source code for "Distilling Knowledge From Graph Convolutional Networks", CVPR'20
  ☆58Updated last year
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆45Updated 4 years ago
• mil-tokyo / hyperbolic_nn_plusplus
  Official PyTorch implementation of Hyperbolic Neural Networks++
  ☆67Updated 3 years ago
• HongtengXu / gwl
  Gromov-Wasserstein Learning for Graph Matching and Node Embedding
  ☆72Updated 5 years ago
• mlvlab / SELAR
  Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
  ☆53Updated 3 years ago
• MinaGhadimiAtigh / hyperbolic_representation_learning
  The repository for Hyperbolic Representation Learning for Computer Vision, ECCV 2022
  ☆62Updated 2 years ago
• zengyi-li / NMCE-release
  Code for Neural Manifold Clustering and Embedding
  ☆57Updated 2 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆61Updated 4 years ago
• Westlake-AI / Markov-Lipschitz-Deep-Learning
  ☆44Updated 4 years ago
• allenhaozhu / COLES
  ☆21Updated 3 years ago
• HongtengXu / Relational-Factorization-Model
  Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)
  ☆31Updated 2 years ago
• ggoh29 / Simplicial-neural-network-benchmark
  Simplicial neural network benchmarking software
  ☆17Updated 2 years ago
• hans66hsu / GATS
  Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)
  ☆22Updated last year
• xiaoiker / Awesome-Hyperbolic-NeuralNetworks
  Papers and Codes for the deep learning in hyperbolic space
  ☆172Updated 2 years ago
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆36Updated last year
• Sherrylone / Zero-CL
  ICLR 2022 paper
  ☆15Updated 2 years ago
• claying / GCKN
  Pytorch Implementation of Graph Convolutional Kernel Networks
  ☆54Updated 2 years ago
• CheriseZhu / GIL
  The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)
  ☆45Updated 4 years ago
• bit-ml / DyReg-GNN
  ☆13Updated 3 years ago
• guoji-fu / pGNNs
  [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks
  ☆27Updated 2 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• DongkiKim95 / D-SLA
  Official Code Repository for the paper "Graph Self-supervised Learning with Accurate Discrepancy Learning" (NeurIPS 2022)
  ☆17Updated 2 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆32Updated 4 years ago
• nmonath / hyperbolic_hierarchical_clustering
  Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Z…
  ☆44Updated 4 years ago