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 ...
Nature

Autoencoder Techniques in Anomaly Detection and Feature Learning

Autoencoders are a class of unsupervised neural networks designed to learn efficient data representations by encoding inputs into a compact latent space and then reconstructing them. Their versatility ...
Nature

A multilayer deep autoencoder approach for cross layer IoT attack detection using deep learning algorithms

IoT networks’ intrinsic complexity and variety make cross-layer-based IoT threat detection vital for defending IoT ecosystems. Security techniques that use a cross-layer approach might identify ...
Psychology Today

Anomaly Detection: The Art of Noticing the Unexpected

Unlike pattern-matching, which is about spotting connections and relationships, when we detect anomalies we are seeing disconnections—things that do not fit together. Anomalies get much less attention ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

The Data Science Lab 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 ...