Alternatives and similar repositories for mctorch

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

• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆130Updated 5 years ago
• cybertronai / pytorch-sso
  PyTorch-SSO: Scalable Second-Order methods in PyTorch
  ☆148Updated 2 years ago
• nicola-decao / BNAF
  Pytorch implementation of Block Neural Autoregressive Flow
  ☆181Updated 4 years ago
• mfinzi / LieConv
  ☆273Updated 2 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆102Updated 7 years ago
• mariogeiger / hessian
  hessian in pytorch
  ☆187Updated 5 years ago
• nicola-decao / power_spherical
  Pytorch implementation of the Power Spherical distribution
  ☆74Updated last year
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 6 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆147Updated last year
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆109Updated 5 years ago
• ParthaEth / Regularized_autoencoders-RAE-
  ☆125Updated 2 years ago
• senya-ashukha / real-nvp-pytorch
  Real NVP PyTorch a Minimal Working Example | Normalizing Flow
  ☆142Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆86Updated 5 years ago
• josipd / torch-two-sample
  A PyTorch library for two-sample tests
  ☆241Updated 2 months ago
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆241Updated 7 years ago
• google-research / ott
  ☆214Updated 3 years ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆231Updated 5 years ago
• google-deepmind / mc_gradients
  ☆172Updated last year
• riannevdberg / sylvester-flows
  ☆181Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆82Updated 6 years ago
• rtqichen / residual-flows
  code for "Residual Flows for Invertible Generative Modeling".
  ☆273Updated 2 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆78Updated 6 years ago
• Thrandis / EKFAC-pytorch
  Repository containing Pytorch code for EKFAC and K-FAC perconditioners.
  ☆149Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆125Updated 2 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆85Updated 4 years ago
• toiaydcdyywlhzvlob / backpack
  This repository is no longer maintained. Check
  ☆81Updated 5 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago