3 papers
math.DS2025
An output scaling layer boosts deep neural networks for multiscale ODE systems
Yuxiao Yi, Weizong Wang, Tianhan Zhang +1
Simulating complex diffusion-reaction systems is often prohibitively expensive due to the high dimensionality and stiffness of the underlying ODEs, where state variables may span t…
astro-ph.IM2025
Deep Neural Networks for Modeling Astrophysical Nuclear Reacting Flows
Xiaoyu Zhang, Yuxiao Yi, Lile Wang +3
In astrophysical simulations, nuclear reacting flows pose computational challenges due to the stiffness of reaction networks. We introduce neural network-based surrogate models usi…
math.NA2025
Solving multiscale dynamical systems by deep learning
Junjie Yao, Yuxiao Yi, Liangkai Hang +5
Multiscale dynamical systems, modeled by high-dimensional stiff ordinary differential equations (ODEs) with wide-ranging characteristic timescales, arise across diverse fields of s…