Gaussian Radial Interaction Kernels as a Unifying Modeling Structure Across Physical and Information Systems
Abstract
Overview: This research explores the application of Gaussian Radial Interaction Kernels as a foundational element for unifying disparate modeling techniques in physics and information science. Key Themes: Universality: Why Gaussian kernels appear naturally across physical scales. Mathematical Synergy: Bridging the gap between radial basis functions and physical interaction laws. Applications: Insights for researchers in computational physics, information theory, and systems modeling.
Fields of Study & Subjects
Neural Networks and Applications
Gaussian Processes and Bayesian Inference
Machine Learning and ELM
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 January 2026
- Language
- EN
- Document type
- Preprint