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 ...

Article Highlight | 3-Nov-2023 Deep variational autoencoder for proteomics mass spectrometry data analysis Research image: Figure 1. Schematic diagram of Dear-DIA. view more Credit: Research ...

In this article, a conditional variational autoencoder based method is proposed for the probabilistic wind power curve modeling task. To advance the modeling performance, the latent random variable is ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

Adversarial examples can be imperceptible to human eyes but can easily fool deep models. Such intrigue property has raised security issues for real-world industrial deep learning systems. To combat ...