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 ...

This GitHub repository contains two directories : (1) variational autoencoder (VAE) and (2) denoising convolutional VAE (DCVAE). This contains programs for VAE and DCVAE models used in our work. For ...

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 ...

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 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 ...

The team proposes an explicit and interpretable discrete variational auto-encoder model for generating efficiency-improving code transformations. They demonstrate that this model can be trained from a ...

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 ...