Abstract: Aeromagnetic gradient tensor (AMGT) interpolation is a critical but challenging step in geophysical data processing, essential for transforming sparse, nonplanar survey data into regular ...
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 ...
The simplified reference tissue model (SRTM) is widely used for PET receptor quantification but assumes constant kinetic parameters. Existing time-varying extensions often impose fixed response shapes ...
Sustainable Dyeing Process Modeling for Recycled PET/PCT Microfibers via Gaussian Process Regression
Department of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea Graduate School of Semiconductor Materials and Devices ...
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 ...
ABSTRACT: We introduce the Kernel-based Partial Conditional Mean Dependence, a scalar-valued measure of conditional mean dependence of Y given X , while adjusting for the nonlinear dependence on Z .
Abstract: Accurate time series forecasting is crucial for optimizing resource allocation, industrial production, and urban management, particularly with the growth of cyber-physical and IoT systems.
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 ...
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