sootlasten / beta-vaeLinks
Beta-VAE implementations in both PyTorch and Tensorflow
☆22Updated 7 years ago
Alternatives and similar repositories for beta-vae
Users that are interested in beta-vae are comparing it to the libraries listed below
Sorting:
- Implementation of the MMD VAE paper (InfoVAE: Information Maximizing Variational Autoencoders) in pytorch☆42Updated 4 years ago
- Disentangled Variational AutoEncoder with PyTorch☆29Updated 6 years ago
- Variational Autoencoders with Gaussian Mixture Latent Space☆36Updated 8 years ago
- Implementation of Hierarchical Long-term Video Prediction without Supervision☆89Updated 3 years ago
- An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…☆72Updated 7 years ago
- ☆17Updated 7 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆87Updated 6 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 6 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆48Updated 7 years ago
- A PyTorch implementation of the blocks from the _A Simple Neural Attentive Meta-Learner_ paper☆98Updated 7 years ago
- Code for reproducing results from our paper, Robustness of conditional GANs to noisy labels, NIPS 2018☆40Updated 6 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆43Updated 6 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019☆39Updated 5 years ago
- Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling☆92Updated 8 years ago
- ☆86Updated 6 years ago
- Variational Autoencoder with Spatial Broadcast Decoder☆35Updated 6 years ago
- Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching☆27Updated 7 years ago
- Conditional Autoencoders with Adversarial Information Factorization☆72Updated 6 years ago
- Code for the "Neural Expectation Maximization" paper.☆126Updated 2 years ago
- TensorFlow-based implementation of "Attend, Infer, Repeat" paper (Eslami et al., 2016, arXiv:1603.08575).☆42Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Implementation of Sequential Attend, Infer, Repeat (SQAIR)☆97Updated 6 years ago
- Code for the "Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions" paper.☆73Updated 2 years ago
- Pytorch implementation of SCAN: Learning Abstract Hierarchical Compositional Visual Concepts☆21Updated 7 years ago
- The Variational Homoencoder: Learning to learn high capacity generative models from few examples☆34Updated 2 years ago
- PyTorch implementation of the NIPS 2017 paper - Unsupervised Learning of Disentangled Representations from Video☆47Updated 5 years ago
- An adversarial autoencoder implementation in pytorch☆85Updated 6 years ago
- Implementation of a convolutional Variational-Autoencoder model in pytorch.☆74Updated 6 years ago
- ☆91Updated 6 years ago