Visual Studio Magazine

Generating Synthetic Data Using a Variational Autoencoder with PyTorch

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...
Insurancenewsnet.com

Reports from University of Central Florida Highlight Recent Findings in Risk Management (Crash Data Augmentation Using Variational Autoencoder)

2021 MAR 29 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News-- Researchers detail new data in Risk Management. According to news reporting from Orlando, Florida, by NewsRx ...
JSTOR Daily

A Random Variational Principle with Application to Weak Hadamard Differentiability of Convex Integral Functionals

We present a random version of the Borwein-Preiss smooth variational principle, stating that under suitable conditions, the set of minimizers of a perturbed function depending on a random variable, ...
JSTOR Daily

Application of an Ultra Weak Variational Formulation of Elliptic PDES to the Two-Dimensional Helmholtz Problem

A new technique to solve elliptic linear PDEs, called ultra weak variational formulation (UWVF) in this paper, is introduced in [B. Després, C. R. Acad. Sci. Paris, 318 (1994), pp. 939-944]. This ...
Drexel University

Math Colloquium: Variational Problems on Random Structures: Analysis & Applications to Data Science

Abstract: Modern data-acquisition techniques produce a wealth of data about the world we live in. Extracting the information from the data leads to machine learning/statistics tasks such as clustering ...