This repository contains a Jupyter notebook implementing a Vanilla Variational Autoencoder (VAE) for image generation. The VAE is a powerful generative model that learns to encode images into a latent ...

you could change the network architecture in the config.json file run the command python vae_train.py mnist or python vae_train.py faces After training, model parameters are stored and you could ...

2.3 Compositional autoencoder 2.3.1 Architecture. The compositional autoencoder extends the vanilla autoencoder architecture in a way that aims to disentangle the latent space, partitioning the impact ...

Contrastive learning both maximizes the similarity between a sample and its augmentations, and the differences between different samples, which is suitable for improving the detection capability of ...

In this paper, convolution architecture autoencoder, which is more efficient in spatial feature extraction and sparse coding, is proposed. Furthermore, the half space HRRP samples, which is much more ...