For example, you could examine a dataset of credit card transactions to find anomalous items that might indicate a fraudulent transaction. This article explains how to use a PyTorch neural autoencoder ...

For example, sparse autoencoders are used in gene expression data analysis, where they help identify a small number of genes most indicative of certain diseases. A denoising autoencoder is another ...

This is a simple example of using a neural network as an autoencoder without using any machine learning libraries in Python. The input is a 8-bit binary digits and as expected the output is the same 8 ...

An image autoencoder may be used to learn a compressed representation of an image. An autoencoder comprises two parts: an encoder, which learns a representation of the image, using fewer neurons than ...

Autoencoder consists of both encoder and decoder ... Improve the model's ability to handle noisy data and generalize well to unseen examples. Learn robust features that capture the underlying ...

Abstract: This article proposes a new underwater thruster fault detection and identification method based on adversarial variational autoencoder (AdvVAE). Adversarial training and variational ...

For example, you could examine a dataset of credit card transactions to find anomalous items that might indicate a fraudulent transaction. This article explains how to use a PyTorch neural autoencoder ...