Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zürich, Vladimir-Prelog-Weg 1-5/10, Zürich 8093, Switzerland ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

This Unity asset provides an end-to-end, Human-in-the-Loop (HITL) Multi-Objective Bayesian Optimization (MOBO) workflow built on botorch.org. It lets you declare design parameters and objectives in ...

This repository contains experiment that implements Bayesian Optimization (BO) techniques for Conditional Value-at-Risk (CVaR)-based portfolio optimization, inspired by the research paper "Bayesian ...

Background and objective: The increasing global prevalence of diabetes has led to a surge in complications, significantly burdening healthcare systems and affecting patient quality of life. Early ...

1 Department of Civil Engineering, King Saud University, Riyadh, Saudi Arabia 2 Department of Civil, Materials, and Environmental Engineering, The University of Illinois Chicago, Chicago, IL, United ...

Abstract: Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free ...

Heidi S. Enger ’27, an Associate Editorial Editor, is a Social Studies Concentrator in Eliot House. She’s enrolled in Ec10b this semester (don’t ask). Harvard students have to stop treating life like ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...