The embedded Python Processing Engine in InfluxDB 3 allows developers to write Python code that analyzes and acts on time ...

Abstract: Automated anomaly detection in spacecraft telemetry systems is essential for analyzing abnormal events and system failures. A widely adopted strategy is to predict the target time sequences ...

Abstract: Multivariate time series anomaly detection (MTAD) plays a vital role in a wide variety of real-world application domains. Over the past few years, MTAD has attracted rapidly increasing ...

Data scientists have developed various anomaly detection algorithms with individual strengths, such as the ability to detect repeating anomalies, anomalies in non-periodic time series, or anomalies ...

In arXiv, 2022. [paper] Time-series anomaly detection service at microsoft. In KDD, 2019. [paper] Robusttad: Robust time series anomaly detection via decomposition and convolutional neural networks.

Acceldata’s autonomous data solution unlocks a range of agentic data management use cases, offering a robust foundation for AI agents to take real-time action based on multi-variate anomaly detection.

Built on Nvidia’s BlueField data processing units, DOCA Argus enables agentless, real-time threat detection that integrates with existing enterprise security systems without affecting performance.

(Purdue University photo/Yuxuan Liu) Wei Xu, a Purdue electrical and computer engineering doctoral student, said the working prototype of CT-Bound achieves real-time boundary detection under ...