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 ...

Next, Dear-DIA uses a variational autoencoder to extract the peak features of fragment ions and maps the features into Euclidean space, and then clusters the features, with different classes of ...

Methods: We developed a Deep Hierarchical Conditional Variational Autoencoder (CVAE) for de novo ACP design, using transfer learning by initializing the ESM-2 pre-trained encoder. A comprehensive ACP ...

A technical paper titled “Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques” was published by researchers at Commonwealth Scientific and ...

In the present paper, we investigate a generalized differential mixed quasi-variational inequality consisting of a system of an ordinary differential equation and a generalized mixed quasi-variational ...

Jianhui Xu, Feifei Zhang, Hong Shu, Kaiwen Zhong, Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover ...