Abstract: In many real-world engineering applications, optimization problems suffer from high-dimensional mixed (continuous-categorical) variables and expensive performance evaluations, which are ...

A comprehensive Edge AI and IoT anomaly detection system designed for research and educational purposes. This project demonstrates real-time anomaly detection using autoencoder-based models optimized ...

Energy Fault Detector is an open-source Python package for automated anomaly detection in operational data from renewable energy systems and power grids. It uses autoencoder-based normal-behaviour ...

Abstract: Hyperspectral unmixing is significant for advancing remote sensing (RS) applications, aiming at extracting the spectra of pure materials (called endmembers) and obtaining their proportions ...

Project Z-Code is a component of Microsoft’s larger XYZ-code initiative to combine AI models for text, vision, audio, and language. Z-code supports the creation of AI systems that can speak, see, hear ...

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 ...

Over the past decade, RNA sequencing, commonly referred to as RNA-Seq, has emerged as a powerful and significant tool, leading to remarkable advancements in the fields of cancer and tumor research.

Recent advances in functional magnetic resonance imaging (fMRI) have helped elucidate previously inaccessible trajectories of early-life prenatal and neonatal brain development. To date, the ...

State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, P.R. China State Key Laboratory of Oncogenes and Related Genes, ...

Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, ...