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 white paper, Bloomberg researchers show the applicability of deep latent variable models (DLVMs) in ESG datasets, outperforming classical imputation models as well as classical predictive ...

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 ...

Variational approximation methods have become a mainstay of contemporary machine learning methodology, but currently have little presence in statistics. We devise an effective variational ...