Seungjoon (Joon) Lee
Seungjoon (Joon) Lee
Mathematics and Statistics, California State University Long Beach
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Coarse-scale PDEs from fine-scale observations via machine learning
S Lee, M Kooshkbaghi, K Spiliotis, CI Siettos, IG Kevrekidis
Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (013141), 2020
Linking Gaussian process regression with data-driven manifold embeddings for nonlinear data fusion
S Lee, F Dietrich, GE Karniadakis, IG Kevrekidis
Interface focus 9 (3), 20180083, 2019
Some manifold learning considerations toward explicit model predictive control
RJ Lovelett, F Dietrich, S Lee, IG Kevrekidis
AIChE Journal 66 (5), e16881, 2020
A general CFD framework for fault-resilient simulations based on multi-resolution information fusion
S Lee, I Kevrekidis, G, G Karniadakis, E
Journal of Computational Physics 347, 290-304, 2017
A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion
S Lee, I Kevrekidis, G, G Karniadakis, E
journal of computational physics 344, 516-533, 2017
Numerical simulation of atomic layer deposition for thin deposit formation in a mesoporous substrate
L Zhuang, P Corkery, DT Lee, S Lee, M Kooshkbaghi, Z Xu, G Dai, ...
AIChE Journal 67 (8), e17305, 2021
Data-driven blended equations of state for condensed-phase explosives
K Lee, AM Hernández, DS Stewart, S Lee
Combustion Theory and Modelling 25 (3), 413-435, 2021
Learning black-and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data
S Lee, YM Psarellis, CI Siettos, IG Kevrekidis
Journal of Mathematical Biology 87 (1), 15, 2023
Resilient algorithms for reconstructing and simulating gappy flow fields in CFD
S Lee, IG Kevrekidis, GE Karniadakis
Fluid Dynamics Research 47 (5), 051402, 2015
Data-driven discovery of chemotactic migration of bacteria via machine learning
YM Psarellis, S Lee, T Bhattacharjee, SS Datta, JM Bello-Rivas, ...
arXiv preprint arXiv:2208.11853, 2022
Prediction of dislocation-grain boundary interactions in FCC aluminum bicrystals using a modified continuum criterion and machine learning methods
JD Gravell, J Cho, S Lee, S Aubry, I Ryu
Materialia 31, 101874, 2023
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–11