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Zhe Bai
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Cited by
Year
Dynamic mode decomposition for compressive system identification
Z Bai, E Kaiser, JL Proctor, JN Kutz, SL Brunton
AIAA Journal 58 (2), 561-574, 2020
902020
Low-dimensional approach for reconstruction of airfoil data via compressive sensing
Z Bai, T Wimalajeewa, Z Berger, G Wang, M Glauser, PK Varshney
AIAA journal 53 (4), 920-933, 2015
822015
Data-driven methods in fluid dynamics: Sparse classification from experimental data
Z Bai, SL Brunton, BW Brunton, JN Kutz, E Kaiser, A Spohn, BR Noack
Whither turbulence and big data in the 21st century?, 323-342, 2017
542017
Non-intrusive Nonlinear Model Reduction via Machine Learning Approximations to Low-dimensional Operators
Z Bai, L Peng
Adv. Model. and Simul. in Eng. Sci. 8 (1), 28, 2021
132021
Randomized methods to characterize large-scale vortical flow networks
Z Bai, NB Erichson, M Gopalakrishnan Meena, K Taira, SL Brunton
PloS one 14 (11), e0225265, 2019
102019
Physics based compressive sensing approach applied to airfoil data collection and analysis. AIAA Paper 2013-0772
Z Bai, T Wimalajeewa, Z Berger, G Wang, M Glauser, PK Varshney
51st Aerospace Sciences Meeting, 2013
8*2013
Physics based compressive sensing approach applied to airfoil data collection and analysis
Z Bai, T Wimalajeewa, ZP Berger, G Wang, M Glauser, PK Varshney
51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and …, 2013
72013
Towards fast and accurate predictions of radio frequency power deposition and current profile via data-driven modelling: applications to lower hybrid current drive
GM Wallace, Z Bai, R Sadre, T Perciano, N Bertelli, S Shiraiwa, EW Bethel, ...
Journal of Plasma Physics 88 (4), 895880401, 2022
42022
AutoCT: Automated CT registration, segmentation, and quantification
Z Bai, A Essiari, T Perciano, KE Bouchard
SoftwareX 26, 101673, 2024
2024
Overview and findings of the FES Scientific Machine Learning project," Accelerating radio frequency modeling using machine learning"
J Wright, Z Bai, G Wallace, N Bertelli, T Perciano, S Shiraiwa, ...
Bulletin of the American Physical Society, 2023
2023
Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models
GM Wallace, Z Bai, N Bertelli, EW Bethel, T Perciano, S Shiraiwa, ...
AIP Conference Proceedings 2984 (1), 2023
2023
Methodology for surrogate modeling implementation: application to the ICRF wave absorption forward problem
Á Sánchez Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
APS Division of Plasma Physics Meeting Abstracts 2023, BO05. 015, 2023
2023
Development of surrogate models for the TORIC ICRF spectrum solver using ML algorithms
Á Sánchez Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
APS Division of Plasma Physics Meeting Abstracts 2023, NP11. 048, 2023
2023
Fusion RF Modeling Machine Learning (FusionML_RF) v1. 0
Z Bai, R Sadre, T Perciano, E Bethel, G Wallace, J Wright, S Shiraiwa, ...
Princeton Univ., NJ (United States); Massachusetts Inst. of Technology (MIT …, 2022
2022
Towards Fast and Accurate Predictions of Radio Frequency Power Deposition and Current Profile via Data-driven Modeling
GM Wallace, Z Bai, N Bertelli, EW Bethel, T Perciano, R Sadre, S Shiraiwa, ...
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States …, 2022
2022
Machine learning models for inverse and lateral problems of lower hybrid current drive
G Wallace, Z Bai, T Perciano, N Bertelli, S Shiraiwa, W Bethel, J Wright
APS Division of Plasma Physics Meeting Abstracts 2022, PP11. 078, 2022
2022
Adaptable Deep Learning and Probabilistic Graphical Model System for Semantic Segmentation
M Avaylon, R Sadre, Z Bai, T Perciano
Advances in Artificial Intelligence and Machine Learning 2 (01), 288-302, 2022
2022
Automated CT registration, segmentation, and quantification (AutoCT) v1. 0
A Essiari, Z Bai, TPC Leite, K Bouchard
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States), 2021
2021
Automated CT registration, segmentation, and quantification (AutoCT) v1. 1
Z Bai, A Essiari, T Perciano Costa Leite, K Bouchard
Lawrence Berkeley National Lab.(LBNL), Berkeley, CA (United States), 2021
2021
Overview and status of the FES Scientific Machine Learning project,''Accelerating radio frequency modeling using machine learning''
J Wright, G Wallace, W Bethel, Z Bai, T Perciano, R Sadre, N Bertelli, ...
APS Division of Plasma Physics Meeting Abstracts 2021, TM10. 002, 2021
2021
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