IEEE

OD-TGCN: An Observer-Driven Temporal Graph Convolutional Network for Early Fault Detection of Control Systems

Abstract: Early faults, with their small amplitudes and slow variations, are easily masked by noise or process trends, making detection difficult. Also, observer-based methods struggle with timely and ...
IEEE

Causal Adjacency Learning for Spatiotemporal Prediction Over Graphs

Abstract: Spatiotemporal prediction over graphs (STPG) is crucial for transportation systems. In existing STPG models, an adjacency matrix is an important component that captures the relations among ...

Allies and algorithms: The matrix and partnerships shaping AI’s future

CNBC's Squawk Box Asia Martin Soong and Chery Kang talk about AMD's chip supply deal with OpenAI, plus the web of alliances, ...
PC Magazine

The Best Encryption Software for 2025

I've been writing and editing stories for almost two decades that help people use technology and productivity techniques to work better, live better, and protect their privacy and personal data. As ...
C&EN

Evaluating Machine Learning Models for Molecular Property Prediction: Performance and Robustness on Out-of-Distribution Data

Department of Pharmaceutical Sciences, Division of Pharmaceutical Chemistry, Faculty of Life Sciences, University of Vienna, Josef-Holaubek-Platz 2, 1090 Vienna, Austria Christian Doppler Laboratory ...
Frontiers

A hypergraph neural network for prioritizing Alzheimer’s disease risk genes

Identifying the complex genetic architecture of Alzheimer’s disease (AD) is critical for understanding its pathophysiology. While network-based computational methods assist in this task, they ...