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 ...

A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...

Understanding the structure of our universe and the distribution of matter is an area of active research. As cosmological surveys grow in complexity, the development of emulators to efficiently and ...

Abstract: Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.