This example shows how to detect out-of-distribution text data using a variational autoencoder (VAE). An encoder that encodes data in a lower-dimensional parameter space. A decoder that reconstructs ...

These methods belong to the field of machine learning, however there are also many ... we will apply three different autoencoders which are simple autoencoder, deep fully-connected autoencoder and ...

In this paper, we propose a deep learning-based transceiver design for secrecy systems as an alternative. Specifically, we modify the loss function design of a variational autoencoder, which is a ...

In this article, we propose a variational autoencoder-enhanced deep learning model (VAEDLM) for wafer defect imbalanced classification. It is light-weighted and effective in wafer defect pattern ...

Moreover, to evaluate the quality of deep learning models, two distance-based metrics ... The dimension of the latent space is set to 2. The variational autoencoder with 4 hidden layers performed the ...

Jianwei Shuai's team and Jiahuai Han's team at Xiamen University have developed a deep autoencoder-based ... Next, Dear-DIA uses a variational autoencoder to extract the peak features of fragment ...

This application of the "Variational AutoEncoder" deep-learning model is an example of how machine learning can be used to interpret and extract meaning from difficult data sets that are too ...