Unit-free theorem pinpoints key variables for AI and physics models

Machine learning models are designed to take in data, to find patterns or relationships within those data, and to use what ...
IEEE

A Gaussian Process-Regularized Graphical Learning Method for Distribution System State Estimation Using Extremely Scarce State Variable Labels

Abstract: Learning-based distribution system state estimation (DSSE) methods typically depend on sufficient fully labeled data to construct mapping functions. However, collecting historical labels ...
IEEE

Multi-Frequency Neural Born Iterative Method for Solving 2-D Inverse Scattering Problems

Abstract: In this work, we propose a deep learning-based imaging method for addressing the multi-frequency electromagnetic (EM) inverse scattering problem (ISP). By combining deep learning technology ...
Yahoo Finance

MicroCloud Hologram Inc. Studies Quantum Computing Methods Based on the Universal Quantum Variable Form, Multi-Quantum Variable Compatibility and Adaptive Measurement

SHENZHEN, China, Oct. 07, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), is a technology service provider. Regarding the optimization problem of variable ...
Phys.org

AI techniques excel at solving complex equations in physics, especially inverse problems

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...