3 papers
math.NA2026
ResiPhy-MDNF: A Residual-Based Physics-Aware Multilevel Discrete Neural Field Framework for PDE-Constrained Inverse Problems
Zheng Lu, Jiwei Jia, Young Ju Lee
Inverse problems governed by partial differential equations are difficult when observations are sparse and the unknown coefficient field contains both large- and small-scale struct…
physics.flu-dyn2026
Invariant Guided PINN for Fluid Flow Computation
Zheng Lu, Jiwei Jia, Bora Aniruddha +2
Physics-informed neural networks (PINNs) often become difficult to optimize for incompressible flow problems with large spatial domains, multiscale stresses, or long-time invariant…
physics.comp-ph2022
Helicity-conservative Physics-informed Neural Network Model for Navier-Stokes Equations
Jiwei Jia, Young Ju Lee, Ziqian Li +2
We design the helicity-conservative physics-informed neural network model for the Navier-Stokes equation in the ideal case. The key is to provide an appropriate PDE model as loss f…