3 papers
cs.LG2026
Tackling multiphysics problems via finite element-guided physics-informed operator learning
Yusuke Yamazaki, Reza Najian Asl, Markus Apel +2
This work presents a finite element-guided physics-informed operator learning framework for multiphysics problems with coupled partial differential equations (PDEs) on arbitrary do…
cs.LG2025
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary Geometries
Reza Najian Asl, Yusuke Yamazaki, Kianoosh Taghikhani +3
In this work, we introduce implicit Finite Operator Learning (iFOL) for the continuous and parametric solution of partial differential equations (PDEs) on arbitrary geometries. We…
cs.LG2025
Neural-Initialized Newton: Accelerating Nonlinear Finite Elements via Operator Learning
Kianoosh Taghikhani, Yusuke Yamazaki, Jerry Paul Varghese +3
We propose a Newton-based scheme, initialized by neural operator predictions, to accelerate the parametric solution of nonlinear problems in computational solid mechanics. First, a…