Machine learning rediscovers equations governing ocean biogeochemistry

Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...
Scientific Research Publishing

Rasmussen, C.E. and Williams, C.K.I. (2006) Gaussian Processes for Machine Learning. The MIT Press.

ABSTRACT: Bipolar disorder (BD) affects approximately 45 million individuals worldwide and is characterized by recurrent episodes of mania, hypomania, and depression, with an average diagnostic delay ...
EurekAlert!

Advances in adsorption processes driven by machine learning

This paper systematically reviews the research progress and application of machine learning in adsorption processes. By virtue of outstanding nonlinear modeling and data mining capabilities, machine ...
eLife

Learning sequence-function relationships with scalable, interpretable Gaussian processes

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 ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
Phys.org

Gaussian processes provide a new path toward quantum machine learning

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 ...
IEEE

Gaussian Process-Based Nonlinear Moving Horizon Estimation

Abstract: In this paper, we propose a novel Gaussian process-based moving horizon estimation (MHE) framework for unknown nonlinear systems. On the one hand, we approximate the system dynamics by the ...
Science Daily

Machine learning simplifies industrial laser processes

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...
C&EN

Bayesian Optimization with Gaussian Processes Assisted by Deep Learning for Material Designs

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Developing novel materials drives significant breakthroughs ...
IEEE

Spatial Modeling with Automated Machine Learning and Gaussian Process Regression Techniques for Imputing Wafer Acceptance Test Data

Abstract: The Wafer Acceptance Test (WAT) is a significant quality control measurement in the semiconductor industry. However, because the WAT process can be time-consuming and expensive, sampling ...