In this work we introduce a novel hybrid architecture, Implicit Discriminator in Variational Autoencoder (IDVAE), that combines a VAE and a GAN, which does not need an explicit discriminator network.

Include the Discriminator network.) The architecture consists of a Variational Autoencoder (VAE) acting as the generator and a Discriminator network. The VAE is trained to generate realistic images, ...

VAE Generator: A Variational Autoencoder that learns to reconstruct normal images. It consists of an encoder and a decoder network. PatchGAN Discriminator: A discriminator network from CycleGAN that ...

which consists of three modules (autoencoder, discriminator, and outlier detector). The ECG-AAE framework is trained only with normal ECG data. Normal ECG signals could be mapped into latent feature ...

The goal of the autoencoder is to minimize the reconstruction ... with a minimal loss of information. The architecture is composed of two components: Encoder - performs compression Decoder ...