IEEE

STAD: Self-Supervised Transformer for Anomaly Detection in Multi-Variate Time Series Data

Abstract: Anomaly detection in multivariate time series has gained significant attention in past few years. The rarity of anomalies, considerable data volatility, absence of anomaly labels, and need ...
GitHub

Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

07.2025: Dinomaly has been integrated in Intel open-edge Anomalib in v2.1.0. Great thanks to the contributors for the nice reproduction and integration. Anomalib is a comprehensive library for ...

Quesma Releases OTelBench: Independent Benchmark Reveals Frontier LLMs Struggle with Real-World SRE Tasks

New benchmark shows top LLMs achieve only 29% pass rate on OpenTelemetry instrumentation, exposing the gap between ...
Visual Studio Magazine

Microsoft Expands Quantum Development Kit with New Open-Source Tools, VS Code Integration

Microsoft released new open‑source quantum development tools that deepen VS Code and Copilot integration while targeting real ...
IEEE

Detectability Driven Recommendation of Anomaly Detection Models for Time-Series Data

Abstract: Anomaly detection for time-series data has been viewed widely in many practical applications and caused lots of research interests. A popular solution based on deep learning techniques is ...