Alternatives and similar repositories for Intrinsic-Dimension

Users that are interested in Intrinsic-Dimension are comparing it to the libraries listed below

• google / wasserstein-dist
  tensorflow implementation of the Wasserstein (aka optimal transport) distance
  ☆72Updated 4 years ago
• LCSL / FALKON_paper
  FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"
  ☆30Updated 4 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆91Updated 7 years ago
• matthieuheitz / WassersteinDictionaryLearning
  Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…
  ☆20Updated 5 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆56Updated 6 years ago
• smortezavi / Randomized_SVD_GPU
  Attempt to speed Randomized SVD(Singular Value Decomposition) Using pytorch and it's gnu capabilities.
  ☆17Updated 7 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• lixilinx / psgd_tf
  Tensorflow implementation of preconditioned stochastic gradient descent
  ☆34Updated last year
• jayanthkoushik / torch-gel
  Group elastic net implementation in PyTorch.
  ☆45Updated 4 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆77Updated last year
• stat-ml / GeoMLE
  This repo contains code for GeoMLE intrinsic dimension estimation algorithm
  ☆20Updated 5 years ago
• karlnapf / kernel_goodness_of_fit
  Code for the paper "A Kernel Test of Goodness of Fit" by Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton
  ☆24Updated 9 years ago
• erichson / ristretto
  Randomized Dimension Reduction Library
  ☆115Updated 4 years ago
• xbresson / IPAM_Tutorial_2019
  Notebooks for IPAM Tutorial, March 15 2019
  ☆24Updated 6 years ago
• lzzcd001 / ade-code
  Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)
  ☆13Updated 5 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆119Updated 2 years ago
• brain-research / conv-sv
  The Singular Values of Convolutional Layers
  ☆72Updated 6 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• PrincetonLIPS / RandomizedAutomaticDifferentiation
  Experiment code for "Randomized Automatic Differentiation"
  ☆67Updated 5 years ago
• izmailovpavel / TTGP
  ☆26Updated 7 years ago
• artemyk / nonlinearIB
  Nonlinear Information Bottleneck
  ☆54Updated 3 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆80Updated 5 years ago
• hichamjanati / spatio-temporal-alignements
  Spatio-temporal alignements: Optimal transport in space and time
  ☆47Updated 3 months ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• gpeyre / 2016-ICML-gromov-wasserstein
  Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.
  ☆73Updated 8 years ago
• geomstats / applications
  Examples of more involved applications using Geomstats
  ☆32Updated 4 years ago
• danielkunin / Regularized-Linear-Autoencoders
  Loss Landscapes of Regularized Linear Autoencoders
  ☆144Updated 3 years ago
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago