Researchers in Japan have developed an adaptive motion reproduction system that allows robots to generate human-like movements using surprisingly small amounts of training data. Despite rapid advances ...

Abstract: In order to reduce the computational complexity of Gaussian process regression models when solving the sub-problem in large-scale optimization, this study considers the historical Gaussian ...

Zhou and colleagues introduce a series of generalized Gaussian process models for genotype-phenotype mapping. The goal was to develop models that were more powerful than standard linear models, while ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

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 ...

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 ...