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Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...
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 ...
Abstract: Deep Learning based intrusion detection systems are susceptible to adversarial examples which are maliciously perturbed data samples that can cause a trained intrusion detection system to ...
","","This repository contains an autoencoder for multivariate time series forecasting.","It features two attention mechanisms described in *[A Dual-Stage Attention ...
Abstract: Learning-enabled components (LECs) are widely used in cyber-physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level of autonomy ...
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 ...
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