Abstract: This paper introduces a cross-process Bayesian multi-objective collaborative optimization framework to address challenges in semiconductor technology migration. We leverage transfer learning ...

Abstract: Bayesian optimization is commonly used to optimize black-box functions associated with simulations in engineering and science. Bayesian optimization contains two essential components: the ...

Introduction: Advances in automation and AI/ML offer new opportunities for plant science, including design, modeling, and analysis. This study aimed to develop an automated platform for researching ...

Biodesign Center for Bioelectronics and Biosensors, Arizona State University, Tempe, Arizona 85287, United States ...

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...