The variational autoencoder (VAE) has proven highly effective in monitoring nonlinear stochastic processes, primarily under the assumption of complete and temporally independent data. However, ...

A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides.. If you have the appropriate software installed, you can download article citation data ...

The study introduces a novel hybrid Variational Autoencoder-SURF (VAE-SURF) model for anomaly detection in crowded environments, addressing critical challenges such as scale variance and temporal ...

The variational autoencoder models the underlying unknown data distribution as conditionally Gaussian, yielding the conditional first and second moments of the estimand, given a noisy observation.

This paper innovatively proposes a temporal–spatial pyramid variational autoencoder (TS-PVAE) model for the nonlinear temporal–spatial feature pyramid extraction from multirate data. This structure ...

Auteurs : BOUTAUD DE LA COMBE Baptiste BOUSSOUF Noâm FAUCHEUX Jérôme PU Zhenyu Ce répertoire est constitué du support de présentation utilisé lors de la soutenance du 22/01/2024 sur les Autoencodeurs ...

In this article, we propose a self-augmentation strategy for improving ML-based device modeling using variational autoencoder (VAE)-based techniques. These techniques require a small number of ...