Alternatives and similar repositories for TopographicVAE

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

• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 2 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 10 months ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆41Updated 6 years ago
• mmrl / disent-and-gen
  Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).
  ☆22Updated 3 years ago
• Lightning-Universe / paper-AAVAE
  ☆47Updated 2 years ago
• facebookresearch / meta-ot
  Meta Optimal Transport
  ☆102Updated 2 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆69Updated 4 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆56Updated 3 years ago
• djordjemila / sdn
  Official PyTorch implementation of Spatial Dependency Networks.
  ☆35Updated 4 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆95Updated 2 years ago
• stanfordmlgroup / disentanglement
  Official repository for our ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology
  ☆36Updated 4 years ago
• nec-research / tf-imle
  Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation
  ☆67Updated 3 years ago
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆84Updated 2 years ago
• dfdazac / vaesbd
  Variational Autoencoder with Spatial Broadcast Decoder
  ☆35Updated 5 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆56Updated 4 years ago
• Alfo5123 / Variational-Sparse-Coding
  Reproducing the paper "Variational Sparse Coding" for the ICLR 2019 Reproducibility Challenge
  ☆62Updated last year
• unixpickle / vq-draw
  A discrete sequential VAE
  ☆39Updated 5 years ago
• larsmaaloee / BIVA
  BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling
  ☆29Updated 5 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated last year
• minyoungg / overparam
  ☆41Updated 2 years ago
• lucidrains / isab-pytorch
  An implementation of (Induced) Set Attention Block, from the Set Transformers paper
  ☆59Updated 2 years ago
• nicola-decao / power_spherical
  Pytorch implementation of the Power Spherical distribution
  ☆74Updated 10 months ago
• choidami / sst
  ☆49Updated 4 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• g-benton / loss-surface-simplexes
  ☆99Updated 3 years ago
• bamos / HowToTrainYourMAMLPytorch
  The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…
  ☆41Updated 4 years ago
• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆45Updated 2 years ago
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆42Updated last year
• lin-shuyu / ladder-latent-data-distribution-modelling
  In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…
  ☆41Updated 4 years ago