At the industry level, the research suggests that AI-enabled decision support could help firms quantify trade-offs more ...

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 ...

MIT researchers used AI to develop novel antibiotics NG1 and DN1, effective against drug-resistant gonorrhoea and MRSA, ...

VAE s replace the simple parametric forms of conventional model equations. They are used for the optimal mapping of complex, high-dimensional market data such as yield-curve and volatility surface to ...

Model architecture Stable Diffusion uses a variational autoencoder (VAE) to generate detailed images from a caption with only a few words. Unlike prior autoencoder-based diffusion models, Stable ...

To understand what, how and when these unlikely incidents might occur, the researchers have used an artificial neural network they call a variational autoencoder (VAE).

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 ...