Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

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 ...
Nature

A multi-information fusion anomaly detection model based on convolutional neural networks and AutoEncoder

Network traffic anomaly detection, as an effective analysis method for network security, can identify differentiated traffic information and provide secure operation in complex and changing network ...
Nature

Improving the explainability of autoencoder factors for commodities through forecast-based Shapley values

Machine learning is a well-developed theoretical framework that is a branch of the wide context of artificial intelligence. It aims to use data and algorithmic procedures to mimic the way humans learn ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...