Year: 2026
Type: article
Abstract: Statistical learning can be used for spectrum prediction, significantly reducing the large computational resources required by simulation software. However, traditional statistical learning methods face challenges such as interpretability and issues with prediction accuracy. By combining phenomenological theory with statistical learning, we propose a resonance-informed model that improves the accuracy and interpretability of spectrum predictions.
Source: Frontiers in Nanotechnology
Author: Zijian Zhang
Institution: Huazhong University of Science and Technology
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,077
OpenAlex ID: W7147284444