zecheng zhang

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Guang LinAssociate Dean for Research, Professor of Mathematics, Mech Eng, Statistics, Purdue UniversityVerified email at purdue.edu
Christian MoyaVisiting Assistant Professor, Purdue UniversityVerified email at purdue.edu
yalchin efendievMobil Chair in Computational Science, Professor of Mathematics, Texas A&M UniversityVerified email at math.tamu.edu
Eric ChungThe Chinese University of Hong KongVerified email at math.cuhk.edu.hk
Hayden SchaefferProfessor of Mathematics, UCLAVerified email at ucla.edu
Yuxuan LiuUniversity of California, Los AngelesVerified email at math.ucla.edu
Lu LuAssistant Professor of Statistics and Data Science, Yale UniversityVerified email at yale.edu
Yating WangAssociate Professor, Xi'an Jiaotong UniversityVerified email at xjtu.edu.cn
Tieyong ZengProfessor, Director of CMAI, Department of Mathematics, The Chinese University of Hong KongVerified email at math.cuhk.edu.hk
Wenyuan LiTexas A&M UniversityVerified email at tamu.edu
Quan ZhouStatistics, Texas A&M UniversityVerified email at stat.tamu.edu
Guanxun LiTexas A&M UniversityVerified email at stat.tamu.edu
Amirhossein MollaaliPh.D student, Purdue UniversityVerified email at purdue.edu
Jingmin SunPh.D. Student in Mathematical Science, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Sai-Mang PunQube Research & Technologies
Liu Liu (刘鎏)Department of Mathematics, The Chinese University of Hong KongVerified email at math.cuhk.edu.hk
Zhidong ZhangSchool of Mathematics (Zhuhai), Sun Yat-sen UniversityVerified email at mail.sysu.edu.cn

zecheng zhang

Assistant professor, department of mathematics, Florida State University

Verified email at fsu.edu - Homepage

mathematics of machine learning scientific machine learning numerical analysis


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
B-DeepONet: An enhanced Bayesian DeepONet for solving noisy parametric PDEs using accelerated replica exchange SGLD G Lin, C Moya, Z Zhang Journal of Computational Physics 473, 111713, 2023	48*	2023
NH-PINN: Neural homogenization-based physics-informed neural network for multiscale problems WT Leung, G Lin, Z Zhang Journal of Computational Physics 470, 111539, 2022	36	2022
Learning the dynamical response of nonlinear non-autonomous dynamical systems with deep operator neural networks G Lin, C Moya, Z Zhang Engineering Applications of Artificial Intelligence 125, 106689, 2023	27*	2023
Efficient hybrid explicit-implicit learning for multiscale problems Y Efendiev, WT Leung, G Lin, Z Zhang Journal of Computational Physics 467, 111326, 2022	21	2022
A multi-stage deep learning based algorithm for multiscale model reduction E Chung, WT Leung, SM Pun, Z Zhang Journal of Computational and Applied Mathematics 394, 113506, 2021	19	2021
Computational multiscale methods for quasi-gas dynamic equations B Chetverushkin, E Chung, Y Efendiev, SM Pun, Z Zhang Journal of Computational Physics 440, 110352, 2021	19	2021
Learning algorithms for coarsening uncertainty space and applications to multiscale simulations Z Zhang, ET Chung, Y Efendiev, WT Leung Mathematics 8 (5), 720, 2020	17	2020
BelNet: basis enhanced learning, a mesh-free neural operator Z Zhang, L Wing Tat, H Schaeffer Proceedings of the Royal Society A 479 (2276), 20230043, 2023	16	2023
Multi-agent Reinforcement Learning Aided Sampling Algorithms for a Class of Multiscale Inverse Problems E Chung, WT Leung, SM Pun, Z Zhang Journal of Scientific Computing 96 (2), 55, 2023	15*	2023
Computational multiscale method for parabolic wave approximations in heterogeneous media E Chung, Y Efendiev, SM Pun, Z Zhang Applied Mathematics and Computation 425, 127044, 2022	15	2022
Multi-variance replica exchange SGMCMC for inverse and forward problems via Bayesian PINN G Lin, Y Wang, Z Zhang Journal of Computational Physics 460, 111173, 2022	13	2022
Multi-variance replica exchange stochastic gradient MCMC for inverse and forward Bayesian physics-informed neural network G Lin, Y Wang, Z Zhang arXiv preprint arXiv:2107.06330, 2021	10	2021
A deep neural network approach on solving the linear transport model under diffusive scaling L Liu, T Zeng, Z Zhang arXiv preprint arXiv:2102.12408, 2021	9	2021
Hybrid explicit–implicit learning for multiscale problems with time dependent source Y Efendiev, WT Leung, W Li, Z Zhang Communications in Nonlinear Science and Numerical Simulation 120, 107081, 2023	8	2023
PROSE: Predicting Operators and Symbolic Expressions using Multimodal Transformers Y Liu, Z Zhang, H Schaeffer arXiv preprint arXiv:2309.16816, 2023	6	2023
Theoretical and numerical studies of inverse source problem for the linear parabolic equation with sparse boundary measurements G Lin, Z Zhang, Z Zhang Inverse Problems 38 (12), 125007, 2022	5	2022
Fast replica exchange stochastic gradient Langevin dynamics G Li, G Lin, Z Zhang, Q Zhou arXiv preprint arXiv:2301.01898, 2023	4	2023
A replica exchange preconditioned Crank-Nicolson Langevin dynamic MCMC method for Bayesian inverse problems O Na, Z Zhang, G Lin arXiv preprint arXiv:2210.17048, 2022	4	2022
D2no: Efficient handling of heterogeneous input function spaces with distributed deep neural operators Z Zhang, C Moya, L Lu, G Lin, H Schaeffer arXiv preprint arXiv:2310.18888, 2023	3	2023
Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE Z Zhang, C Moya, WT Leung, G Lin, H Schaeffer arXiv preprint arXiv:2308.14188, 2023	3	2023

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