This paper proposes a complex recurrent variational autoencoder (VAE) framework, for modeling time series data, particularly speech signals. First, to account for the temporal structure of speech ...

This repository contains numerous applications of autoencoder neural networks. Projects include image denoising, detection of infected cells, and processing of the MNIST dataset. Each application ...

This paper addresses the challenge of blind non-linear equalization using a variational autoencoder (VAE) with a second-order Volterra channel model. The VAE framework’s costfunction, the evidence ...

This demo highlights how one can use a semi-supervised machine learning technique based on autoencoder to detect an anomaly in sensor data (output pressure of a triplex pump). The demo also shows how ...

IT4Innovations, VSB─Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic ...