News

Scientific Research Publishing

Machine Learning for Financial Risk Management: Modeling Time-Varying Factor Sensitivities Using Factor Variational Autoencoders ()

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.
Albuquerque Journal

Sandia researchers build AI system to detect anomalies across the electrical grid

This technology is able to detect abnormalities in the grid and help us understand when we’re having a cyber attack or ...
ascopubs.org

A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides.

Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
EurekAlert!

Zhu harnessing interpretable neuro-symbolic learning for reliable ranking

Ziwei Zhu, Assistant Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “III: Small: Harnessing Interpretable Neuro-Symbolic Learning for ...

Jingzhida (688627.SH): Future Layouts Will Focus on AI-Driven High Computing Power, High Storage, and Deep Human-Machine Interaction Needs

On September 11, Gelonghui reported that Jingzhida (688627.SH) stated on its interactive platform that the company continues to innovate technology and develop intellectual property in the ...
Harvard Business School

Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error

Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks ...