In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...
Objective: This study aims to develop an explainable machine learning model, incorporating stacking techniques, to predict the occurrence of liver injury in patients with sepsis and provide decision ...
Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
David J. Silvester, a mathematics professor at the University of Manchester, has developed a novel machine-learning method to ...
Abstract: This paper designs an intelligent prediction model using machine learning technology. By collecting data and extracting features of various parameters of material interface properties (such ...
Abstract: With the rising adoption of deep neural networks (DNNs) for commercial and high-stakes applications that process sensitive user data and make critical decisions, security concerns are ...