That said, applying a neural autoencoder anomaly detection system to tabular data is typically the best way to start. A limitation of the autoencoder architecture presented in this article is that it ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

This repository provides the official Python implementation our KDD 2025 paper: 📄 "Predicting the Dynamics of Complex Systems via Multiscale Diffusion Autoencoder" MDPNet is a novel approach for ...

This project provides an unsupervised learning solution for detecting anomalies in time-series data, specifically demonstrated on synthetic network traffic. It leverages a Long Short-Term Memory (LSTM ...

Abstract: Multifunction radars are highly adaptive systems that employ phased array antennas and can simultaneously perform multiple working modes, such as search, tracking, recognition, and guidance.

Abstract: The reciprocity of wireless channels is a prerequisite for physical layer secret key generation (SKG). However, inherent factors, such as noise, asynchronous observations, and hardware ...