AFTER IMPORTING ALL THE NECESSARY LIBRARIES, TWO PYTHON FILES MADE CVAE_EXP AND CVAE_function. THE FORMER CONTAINS THE AUTOENCODER ARCHITECTURE ... TO FIND THE OPTIMAL HYPERPARAMETERS FOR THE GIVEN ...

Building a Variational Autoencoder (VAE) functionality for MNIST Dataset ... with the objective to minimize the returned value (validation loss) from the objective function. study.optimize runs the ...

However, a fundamental flaw exists in Variational Autoencoder (VAE) based approaches. Specifically, the objective function of VAE (reconstruction loss), deviates from its primary objective (i.e ...

2.1 Improvement of the objective function of the VAE network Inspired ... At the same time, the loss function of the variational autoencoder (VAE) is improved. By adding a hyperparameter β to the ...

A variational autoencoder (VAE) is a deep neural system that can be ... file of UCI digits data into memory as a two-dimensional array using the NumPy loadtxt() function. The pixel values are ...