Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

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 ...
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 ...
Yahoo Finance

Acceldata Launches Industry-First Adaptive AI Anomaly Detection to Accelerate Agentic Data Management

CAMPBELL, Calif., April 29, 2025 (GLOBE NEWSWIRE) -- Acceldata, a leading provider of data observability and agentic data management solutions, today announced Adaptive AI Anomaly Detection, a ...
InfoQ

Fraud Detection Using Random Forest, Neural Autoencoder, and Isolation Forest Techniques

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Dark Reading

IoT Anomaly Detection 101: Data Science to Predict the Unexpected

If you run a quick web search on "machine learning use cases," you will find pages and pages of links to documents describing machine learning (ML) algorithms to detect or predict some kind of event ...
Visual Studio Magazine

Data Anomaly Detection Using a Neural Autoencoder with C#

Data anomaly detection is 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. There are many different types of ...