From the 1 of 5 linked papers with an AI index.
5 papers
Predicting Space Groups of Double Perovskites by LLM with Dynamic Few-Shot Learning
Jongwon Park, Inhyo Lee, Junhyeong Lee +1
Double perovskites (DPs) offer broad compositional tunability, but predicting the space groups (SGs) of stable structures remains difficult because available datasets are often str…
Uncertainty-Aware Structure-Property Mapping of Spinodoid Metamaterials via Heteroscedastic Gaussian Process Regression
Minwoo Park, Junseo Park, Mingyu Lee +4
The paper introduces a framework that uses heteroscedastic Gaussian process regression to model the uncertainty in the relationship between spinodoid metamaterial structures and th…
A Hybrid GNN-FEM Framework for Phase-Field Fracture Simulation. Physics-Preserving Hybridization for Generalizable Surrogate Modeling
Hyeonbin Moon, Yongjin Choi, Seunghwa Ryu
Scientific machine learning (SciML) has emerged as a promising approach for accelerating simulations of complex physical systems, yet achieving physically consistent and generaliza…
Physics-Informed Discovery of Yield Functions in Plasticity via Convex Neural Representations
Hyeonbin Moon, Donghyuk Cho, Jecheon Yu +2
Identifying anisotropic yield functions remains challenging since yielding is not directly observed in full-field mechanical measurements, directional calibration can require many…
Morphology-, Noise-, and Resolution-Robust Ultrasound Elasticity Imaging with Fourier Neural Operators
Heekyu Kim, Hugon LEe, Minwoo Park +1
Ultrasound-based elasticity imaging is a non-invasive technique for estimating tissue stiffness fields from displacement fields obtained by comparing ultrasound signals before and…