Alternatives and similar repositories for tf-fsvd:

Users that are interested in tf-fsvd are comparing it to the libraries listed below

• dgranata / Intrinsic-Dimension
  Python code for intrinsic dimension estimation of generic datasets
  ☆19Updated 6 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆117Updated last year
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆53Updated 2 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• jacobdeasy / geometric-js
  ☆16Updated 3 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆55Updated 3 years ago
• nec-research / tf-imle
  Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
  ☆67Updated 3 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• geomstats / applications
  Examples of more involved applications using Geomstats
  ☆32Updated 4 years ago
• rajesh-lab / deep_permutation_invariant
  Code accompanying paper "Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets."
  ☆22Updated 2 years ago
• nicola-decao / power_spherical
  Pytorch implementation of the Power Spherical distribution
  ☆74Updated 8 months ago
• stat-ml / GeoMLE
  This repo contains code for GeoMLE intrinsic dimension estimation algorithm
  ☆20Updated 4 years ago
• MarcTLaw / UltrahyperbolicRepresentation
  Ultrahyperbolic Representation Learning
  ☆12Updated 4 years ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆21Updated 5 years ago
• matthieuheitz / WassersteinDictionaryLearning
  Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…
  ☆18Updated 5 years ago
• hichamjanati / spatio-temporal-alignements
  Spatio-temporal alignements: Optimal transport in space and time
  ☆43Updated 3 years ago
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 2 years ago
• scottgigante / m-phate
  Multislice PHATE for tensor embeddings
  ☆59Updated 4 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• ExpectationMax / sklearn-jax-kernels
  Composable kernels for scikit-learn implemented in JAX.
  ☆43Updated 4 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆57Updated 3 years ago
• gebob19 / introduction_to_normalizing_flows
  Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'
  ☆25Updated 3 years ago
• geomstats / challenge-iclr-2021
  GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
  ☆49Updated 2 years ago
• dmilios / dirichletGPC
  ☆17Updated 6 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 4 years ago
• danielkunin / Regularized-Linear-Autoencoders
  Loss Landscapes of Regularized Linear Autoencoders
  ☆144Updated 2 years ago
• lzzcd001 / ade-code
  Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)
  ☆13Updated 5 years ago
• cscarv / riemannian-metric-learning-ot
  ☆17Updated last year
• jrmcornish / lgf
  Pytorch implementation of Localised Generative Flows
  ☆11Updated 4 years ago