Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
A data free neural operator enabling fast inference of 2D and 3D Navier Stokes equations
Junho Choi, Teng-Yuan Chang, Namjung Kim +1
Ensemble simulations of high-dimensional flow models (e.g., Navier Stokes type PDEs) are computationally prohibitive for real time applications. Neural operators enable fast infere…
cs.LG2024
MaD-Scientist: AI-based Scientist solving Convection-Diffusion-Reaction Equations Using Massive PINN-Based Prior Data
Mingu Kang, Dongseok Lee, Woojin Cho +5
Large language models (LLMs), like ChatGPT, have shown that even trained with noisy prior data, they can generalize effectively to new tasks through in-context learning (ICL) and p…
cs.LG2023
Spectral operator learning for parametric PDEs without data reliance
Junho Choi, Taehyun Yun, Namjung Kim +1
In this paper, we introduce the Spectral Coefficient Learning via Operator Network (SCLON), a novel operator learning-based approach for solving parametric partial differential equ…