A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data ...

Abstract: This paper proposes a Multi-scale Dilated Variational Graph Convolutional Autoencoder (MG-VAE) model for gas turbine fault diagnosis. The model integrates a multi-scale dilated convolutional ...

This article presents the process of building a system generating polyphonic music content of a specified emotion using a conditional variational autoencoder and convolutional layers. The process of ...

The proposed HcVGH combines a convolutional variational autoencoder (cVAE) with HVGH, a past method, which follows the hierarchical Dirichlet process-variational autoencoder-Gaussian process-hidden ...

The convolutional chain (at the top of the circuit in Figure ... and 24 feature, respectively). The variational autoencoder models for each lead were also trained. Examples of the results of trained ...