This article discusses the use of Bayesian optimization, a machine-learning-based approach, to enhance the critical current properties of K-doped Ba122. The methodology involves a…
Browsing: Bayesian Optimization
This article discusses the use of machine learning for the optimization of polymer-immobilized catalysts, specifically for Suzuki-Miyaura coupling reactions. The study utilizes a Bayesian…
MeV-UED has revolutionized the study of ultrafast structural dynamics, and efficient online beam tuning strategies are highly desired. Multi-objective Bayesian active learning has been…
This article discusses the need for advanced optimization techniques in machine learning, as traditional methods are not sufficient for navigating the complexities of modern…
This article discusses the growing trend of using active learning methods to optimize experimental materials synthesis and characterization. The authors present a human-AI collaborated…
This Special Issue will publish high-quality, original research papers advancing the state of the art in the application of machine learning and/or Bayesian optimization.…
AutoGluon is an open source project that automates machine learning tasks, allowing users to quickly and easily train and deploy high-accuracy models on image,…
AutoGluon is an open-source project that automates machine learning tasks, allowing users to quickly and easily train and deploy high-accuracy models on image, text,…
AutoGluon is an open source project that automates machine learning tasks, allowing users to quickly and easily train and deploy high-accuracy models on image,…
AutoGluon is an open source project that automates machine learning tasks to enable users to easily achieve strong predictive performance in their applications. With…