nnormandin / Conditional_VAE
conditional variational autoencoder written in Keras [not actively maintained]
☆96Updated 7 years ago
Alternatives and similar repositories for Conditional_VAE:
Users that are interested in Conditional_VAE are comparing it to the libraries listed below
- Keras implementation of the paper "Autoencoding beyond pixels using a learned similarity metric"☆54Updated 6 years ago
- Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR1…☆121Updated 6 years ago
- ☆16Updated 6 years ago
- Keras implementation of LSTM Variational Autoencoder☆228Updated 5 years ago
- ☆199Updated 7 years ago
- This repository has implementation and tutorial for Deep Belief Network☆102Updated 6 years ago
- PyTorch implementation of Wasserstein Auto-Encoders☆295Updated 4 years ago
- Keras Implementation of adverserial autoencoder (AAE)☆56Updated 6 years ago
- A wizard's guide to Adversarial Autoencoders☆435Updated 3 years ago
- Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering☆297Updated 7 years ago
- This repository contains the implementation of the VAE and Gaussian Mixture VAE using TensorFlow and several network architectures☆207Updated 4 years ago
- Implementation of simple autoencoders networks with Keras☆241Updated 4 years ago
- Pytorch Adversarial Auto Encoder (AAE)☆87Updated 5 years ago
- Convolutional variational autoencoder in PyTorch☆46Updated 6 years ago
- Variational autoencoder for anomaly detection (in PyTorch).☆48Updated 5 years ago
- A CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch☆299Updated 4 years ago
- Variational Autoencoder for Dimensionality Reduction of Time-Series☆185Updated 2 years ago
- PyTorch implementation of SDAE (Stacked Denoising AutoEncoder)☆124Updated 4 years ago
- VAEGAN from "Autoencoding beyond pixels using a learned similarity metric" implemented in Pytorch. Clean, clear and with comments.☆187Updated 7 years ago
- Semi-supervised learning with mnist using variational autoencoders. An unsupervised representation is learned which allows for superior …☆32Updated 6 years ago
- Wasserstein Auto-Encoders☆507Updated 6 years ago
- Conditional Wasserstein GANs☆73Updated 7 years ago
- A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).☆129Updated 5 years ago
- Implementation of a convolutional auto-encoder in PyTorch☆19Updated 6 years ago
- Stacked denoising convolutional autoencoder written in Pytorch for some experiments.☆127Updated last year
- ☆110Updated 7 years ago
- Implementation of a convolutional Variational-Autoencoder model in pytorch.☆74Updated 5 years ago
- Generative Adversarial Imputation Networks (GAIN) Pytorch version☆29Updated 6 years ago
- Unsupervised clustering with (Gaussian mixture) VAEs☆297Updated 8 years ago
- Replication of Semi-Supervised Learning with Deep Generative Models☆98Updated 8 years ago