HazyResearch / HypHC

Related projects: ⓘ

• HazyResearch / HoroPCA
  Hyperbolic PCA via Horospherical Projections
  ☆68Updated last year
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆123Updated 11 months ago
• dalab / hyperbolic_nn
  Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112
  ☆171Updated 3 years ago
• drewwilimitis / hyperbolic-learning
  Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
  ☆126Updated 4 years ago
• facebookresearch / hgnn
  Hyperbolic Graph Neural Networks
  ☆229Updated 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…
  ☆41Updated 4 years ago
• leymir / hyperbolic-image-embeddings
  Supplementary code for the paper "Hyperbolic Image Embeddings".
  ☆363Updated 2 years ago
• HazyResearch / hyperbolics
  Hyperbolic Embeddings
  ☆370Updated last year
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆100Updated 4 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆53Updated 2 years ago
• josipd / torch-two-sample
  A PyTorch library for two-sample tests
  ☆236Updated last year
• muhanzhang / D-VAE
  D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019
  ☆125Updated 3 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆58Updated 3 years ago
• nicola-decao / s-vae-pytorch
  Pytorch implementation of Hyperspherical Variational Auto-Encoders
  ☆348Updated 4 years ago
• rsonthal / TreeRep
  Learning Tree structures and Tree metrics
  ☆22Updated last month
• leowyy / GraphTSNE
  PyTorch Implementation of GraphTSNE, ICLR’19
  ☆133Updated 5 years ago
• Cyanogenoid / dspn
  [NeurIPS 2019] Deep Set Prediction Networks
  ☆100Updated 4 years ago
• ydtydr / HyperbolicTiling_Learning
  Official implementation (learning part) for paper: Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models
  ☆18Updated last month
• tvayer / FGW
  Code for Optimal Transport for structured data with application on graphs
  ☆95Updated last year
• lucfra / LDS-GNN
  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)
  ☆190Updated 6 months ago
• dalab / hyperbolic_cones
  Source code for the ICML'18 paper "Hyperbolic Entailment Cones for Learning Hierarchical Embeddings", https://arxiv.org/abs/1804.01882
  ☆128Updated 6 years ago
• BorgwardtLab / WWL
  Wasserstein Weisfeiler-Lehman Graph Kernels
  ☆77Updated 2 weeks ago
• ParthaEth / Regularized_autoencoders-RAE-
  ☆120Updated last year
• BorgwardtLab / topological-autoencoders
  Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
  ☆138Updated 2 years ago
• ermongroup / graphite
  Code for Graphite iterative graph generation
  ☆56Updated 5 years ago
• mil-tokyo / hyperbolic_nn_plusplus
  Official PyTorch implementation of Hyperbolic Neural Networks++
  ☆63Updated 3 years ago
• ferrine / hyrnn
  Hyperbolic Neural Networks, pytorch
  ☆83Updated 5 years ago
• lsj2408 / GraphNorm
  [ICML 2021] GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training (official implementation)
  ☆99Updated last year
• BorgwardtLab / TOGL
  Topological Graph Neural Networks (ICLR 2022)
  ☆109Updated 2 years ago
• snap-stanford / comet
  [ICLR 2021] Concept Learners for Few-Shot Learning
  ☆111Updated last year