Mathematicians finally understand the behavior of an important class of differential equations that describe everything from ...
ABSTRACT: Machine learning (ML) has become an increasingly central component of high-energy physics (HEP), providing computational frameworks to address the growing complexity of theoretical ...
This repository contains all the various and noteworthy short simple codes (in Python 3.13.5, Jupyter Notebook 7.4.5, Mathematica 13.3, R 4.4.2, and Julia 1.11.3) I have ever made while studying for ...
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands The rapid growth of large-scale neuroscience datasets has spurred diverse modeling strategies, ranging ...
If you find these results useful, please cite the article mentioned above. If you use the implementations provided here, please also cite this repository as We develop structure-preserving numerical ...
Light Publishing Center, Changchun Institute of Optics, Fine Mechanics And Physics, CAS Four decades ago, Feynman proposed the idea that the operation of a complex quantum system can be simulated by ...
Abstract: The differential equation-based image restoration approach aims to establish learnable trajectories connecting high-quality images to a tractable distribution, e.g., low-quality images or a ...
Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. Once a well-suited model is established, it can be thoroughly ...
Abstract: Many problems in science and engineering can be mathematically modeled using partial differential equations (PDEs), which are essential for fields like computational fluid dynamics (CFD), ...
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