Alternatives and similar repositories for hyplinear

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

• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆60Updated 4 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆59Updated 4 years ago
• ferrine / hyrnn
  Hyperbolic Neural Networks, pytorch
  ☆87Updated 6 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆37Updated 5 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• kingofspace0wzz / wae-rnf-lm
  Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…
  ☆63Updated 5 years ago
• oskopek / mvae
  Mixed-curvature Variational Autoencoders (ICLR 2020)
  ☆65Updated 4 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago
• claying / OTK
  A Pytorch implementation of the optimal transport kernel embedding
  ☆118Updated 4 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 2 years ago
• dalab / hyperbolic_nn
  Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112
  ☆181Updated 5 years ago
• google / gumbel_sinkhorn
  ☆76Updated 8 years ago
• gabsens / Learning-Embeddings-into-Entropic-Wasserstein-Spaces-ENSAE
  A thorough review of the paper "Learning Embeddings into Entropic Wasserstein Spaces" by Frogner et al. Includes a reproduction of the re…
  ☆22Updated 5 years ago
• ec6dde01667145e58de60f864e05a4 / CausalOptimizationAnon
  ☆65Updated last year
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆41Updated 2 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• sidak / context-mover-distance-and-barycenters
  Code accompanying our paper at AISTATS 2020
  ☆21Updated 4 years ago
• ydtydr / HyperbolicTiling_Learning
  Official implementation (learning part) for paper: Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models
  ☆18Updated last year
• chingyaoc / TMD
  NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks
  ☆37Updated 2 years ago
• giannisnik / repset
  Rep the Set: Neural Networks for Learning Set Representations
  ☆29Updated 5 years ago
• emilemathieu / pvae
  code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".
  ☆129Updated 2 years ago
• rythei / PyTorchOT
  implements optimal transport algorithms in pytorch
  ☆102Updated 3 years ago
• PurdueMINDS / JanossyPooling
  ☆25Updated 6 years ago
• NNReasoning / What-Can-Neural-Networks-Reason-About
  ☆44Updated 5 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• agadetsky / pytorch-pl-variance-reduction
  [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
  ☆39Updated 4 years ago
• ermongroup / neuralsort
  Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.
  ☆146Updated 2 years ago
• nec-research / tf-imle
  Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
  ☆67Updated 3 years ago
• icemiliang / pyvot
  A Python implementation of Monge optimal transportation
  ☆49Updated 2 years ago