Alternatives and similar repositories for challenge-iclr-2022:

Users that are interested in challenge-iclr-2022 are comparing it to the libraries listed below

• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆87Updated last year
• geomstats / challenge-iclr-2021
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆49Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated last year
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆116Updated last year
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 3 years ago
• dimkal89 / rvae
  ☆37Updated 4 years ago
• topnn / topnn_framework
  ☆32Updated 4 years ago
• stefaniaebli / simplicial_neural_networks
  Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…
  ☆76Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 7 months ago
• lezcano / expm
  Differentiable and numerically stable implementation of the matrix exponential
  ☆32Updated 4 years ago
• mfinzi / residual-pathway-priors
  ☆18Updated 3 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆53Updated 2 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆48Updated last year
• pierreablin / ksddescent
  Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities
  ☆21Updated 11 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• ximenafernandez / intrinsicPH
  This is the code related to the article 'Intrinsic persistent homology via density-based metric learning'
  ☆10Updated last year
• pyt-team / TopoEmbedX
  Representation Learning on Topological Domains
  ☆79Updated this week
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆33Updated 4 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆45Updated last year
• BorgwardtLab / Neural-Persistence
  Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'
  ☆30Updated 6 years ago
• pyt-team / challenge-icml-2024
  Official repository for the Topological Deep Learning Challenge 2024, organized by TAG-DS & PyT-Team and hosted by GRaM Workshop @ ICML 2…
  ☆38Updated 3 weeks ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆55Updated 3 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 4 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• BorgwardtLab / topological-autoencoders
  Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.
  ☆143Updated 3 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆57Updated 3 years ago
• c-hofer / torchph
  The essence of my research, distilled for reusability. Enjoy 🥃!
  ☆63Updated 7 months ago