A variational autoencoder (VAE) is one of several generative models that use deep learning to generate new content, detect anomalies and remove noise. Suited for generating synthetic time series data ...

Researchers have developed an unsupervised deep learning model called GSA-VAE that detects faults in electric vehicle ...

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 ...

A new hybrid framework combining a Variational Autoencoder with Proximal Policy Optimization reinforcement learning generates ...

The history of evolution leading to the birth of generative AIAI has developed as a technology for finding human faces in ...

Autoencoders are a common tool for training neural network algorithms, but developers need to be mindful of the challenges that come with using them skillfully. Autoencoders are additional neural ...