The whitepaper represents the first-ever analysis of the impact of stochastics effects from the perspective of resolution. A gap has emerged between the size of features that can be patterned in ...

Under this scenario, stochastic variation in cell cycle length generates a steady-state distribution of cell cycle positions. Optimal proportioning of stalk and spore cells is presumably reached ...

Scenario based stochastic scheduling has drawn a tremendous amount of interests worldwide in tackling the uncertainty of renewable energy and accounting for risks. It is important to generate ...

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 ...

Georgia Tech & Google Propose a Novel Discrete Variational Autoencoder for Automatically Improving Code Efficiency by Synced 2022-08-16 Comments 5 ...

The results above show it should be possible to systematically learn gene regulatory connections from stochastic variation in steady-state cells, provided one can measure transcriptome-wide mRNA ...

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 ...