Alternatives and similar repositories for vaesbd

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

• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 6 years ago
• haoliuhl / hybrid-discriminative-generative
  Hybrid Discriminative-Generative Training via Contrastive Learning
  ☆75Updated 2 years ago
• pemami4911 / EfficientMORL
  EfficientMORL (ICML'21)
  ☆22Updated 4 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆69Updated 5 years ago
• sjoerdvansteenkiste / Relational-NEM
  Code for the "Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions" paper.
  ☆73Updated 3 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• stelzner / monet
  An implementation of the MONet model for unsupervised scene decomposition in PyTorch
  ☆59Updated 3 years ago
• fabienbaradel / cophy
  "CoPhy: Counterfactual Learning of Physical Dynamics", F. Baradel, N. Neverova, J. Mille, G. Mori, C. Wolf, ICLR'2020
  ☆35Updated 5 years ago
• CUAI / BetterSetRepresentations
  [NeurIPS 2020] Better Set Representations For Relational Reasoning (https://arxiv.org/abs/2003.04448)
  ☆31Updated 4 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆58Updated 6 years ago
• rosinality / igebm-pytorch
  Implicit Generation and Generalization in Energy Based Models in PyTorch
  ☆67Updated 6 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆27Updated 6 years ago
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆85Updated 3 years ago
• rr-learning / disentanglement_dataset
  ☆79Updated 7 months ago
• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆43Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• Zhiyuan1991 / proVLAE
  ☆27Updated 5 years ago
• xqding / TD-VAE
  Temporal Difference Variational Auto-Encoder (TD-VAE) (Implementation in PyTorch)
  ☆163Updated 2 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• seuqaj114 / paig
  Code for the paper Physics-as-Inverse-Graphics: Joint Unsupervised Learning of Objects and Physics from Video
  ☆42Updated 2 years ago
• conormdurkan / neural-statistician
  PyTorch Implementation of Neural Statistician
  ☆61Updated 3 years ago
• jlko / STOVE
  Structured Object-Aware Physics Prediction for Video Modeling and Planning
  ☆32Updated 5 years ago
• denproc / Taming-VAEs
  ☆26Updated 6 years ago
• thanard / causal-infogan
  ☆85Updated 6 years ago
• stelzner / supair
  Implementation of Sum-Product Attend-Infer-Repeat
  ☆31Updated 5 years ago
• hschoi1 / rich_latent
  rich posterior approximations and anomaly detection
  ☆20Updated 6 years ago
• kefirski / variational_dropout
  Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
  ☆49Updated 8 years ago
• Cyanogenoid / fspool
  [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling
  ☆41Updated 2 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago