EurekAlert!

Chung-Ang University researchers review deep learning-based methods to detect time series data anomaly

Researchers analyze state-of-the-art approaches, limitations, and applications of deep learning-based anomaly detection in multivariate time series Monitoring financial security, industrial safety, ...

FutureMain Bolsters Global Industrial AI Competitiveness with NPU-Based Time-Series AI Project

FutureMain Co., Ltd., a specialized industrial AI company focused on equipment diagnostics and predictive maintenance, ...
insideHPC

Research Highlights: MIT Develops First Generative Model for Anomaly Detection that Combines both Reconstruction-based and Prediction-based Models

Kalyan Veeramachaneni and his team at the MIT Data-to-AI (DAI) Lab have developed the first generative model, the AutoEncoder with Regression (AER) for time series anomaly detection, that combines ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
InfoWorld

5 ways companies can use time-series forecasting

Recent advances in AI, such as foundation models, make it possible for smaller companies to build custom models to make predictions, reduce uncertainty, and gain business advantage. Time series ...