The variational autoencoder (VAE) has proven highly effective in monitoring nonlinear stochastic processes, primarily under the assumption of complete and temporally independent data. However, ...

Liang, X., Chen, B., Chen, W., Wang, P. and Liu, H. (2022) Unsupervised Radar Target Detection under Complex Clutter Background Based on Mixture Variational Autoencoder.

Scientists complete largest wiring diagram and functional map of the brain to date The MICrONS Project is considered the most complicated neuroscience experiment ever attempted Date: April 9, 2025 ...

   From a tiny sample of tissue no larger than a grain of sand, scientists have come within reach of a goal once thought unattainable: building a complete functional wiring diagram of a ...

This article proposes a novel orthogonal frequency-division multiplexing (OFDM) autoencoder featuring convolutional neural networks (CNNs)-based channel estimation for marine communications with ...

This image illustrates an autoencoder neural network architecture, focusing on the hidden layer role in transforming data into an embedding vector format. It highlights the encoder compression ...

There are many different types of anomaly detection techniques. This article explains how to use a neural autoencoder implemented using raw C# to find anomalous data items. Compared to other anomaly ...

Autoencoder for Product Matching This was an experiment for a possible PhD topic. The main idea was to use different Autoencoder for entity resolution / product matching. The core idea was to pretrain ...