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 special type of ...

Our model is based on a novel Variational Autoencoder (VAE) that encodes a graph and decodes a string, offering advanced polymer design capabilities, including inverse design via optimization in ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data ... in a random order on each pass through the Dataset. The design pattern presented here will work ...

The variational autoencoder with 4 hidden layers performed the best with ... RMSD and the DOPE score were used to quantify structure and system energy differences, respectively. The DOPE score has ...

Over millennia, natural evolution has allowed for the emergence of countless biomolecules with highly specific roles within natural systems. As seen with ... with antimicrobial activity. Using a ...

Classification of power system event data is a growing need ... to classify and label transients observed in the distribution grid. A Convolutional Variational Autoencoder (CVAE) was developed for ...

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 special type of ...