Dongbin Xiu

Oldham Council — United Kingdom

Decision Sciences · Social Sciences

44h-index16.5kcitations189works1.12yr avg
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Research Topics

Probabilistic and Robust Engineering Design(100), Model Reduction and Neural Networks(48), Wind and Air Flow Studies(27), Advanced Multi-Objective Optimization Algorithms(25), Neural Networks and Applications(16)

Publications189 total

LEARNING INVERSE MAPS FOR PARAMETER ESTIMATION IN DYNAMICAL SYSTEMS
Journal of Machine Learning for Modeling and Computing·2026
Targeted Digital Twin via Flow Map Learning and Its Application to Fluid Dynamics
SSRN Electronic Journal·2026Open Access
DUE: A Deep Learning Framework and Library for Modeling Unknown Equations
SIAM Review·2025
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems
SIAM Journal on Scientific Computing·2025
Targeted Digital Twin via Flow Map Learning and Its Application to Fluid Dynamics
arXiv (Cornell University)·2025Open Access
Likelihood-free Posterior Density Learning for Uncertainty Quantification in Inference Problems
arXiv (Cornell University)·2025Open Access
Deep Learning for Model Correction of Dynamical Systems with Data Scarcity
SIAM/ASA Journal on Uncertainty Quantification·2025· 1 cited
DUE: A Deep Learning Framework and Library for Modeling Unknown Equations
arXiv (Cornell University)·2025Open Access
On Enforcing Nonnegativity in Polynomial Approximations in High Dimensions
SIAM Journal on Scientific Computing·2025· 1 cited
Computational Framework For Real-Time Digital Twins
2025· 1 cited
DIMENSION-REDUCED RECONSTRUCTION MAP LEARNING FOR PARAMETER ESTIMATION IN LIKELIHOOD-FREE INFERENCE PROBLEMS
Journal of Machine Learning for Modeling and Computing·2025
CHEBYSHEV FEATURE NEURAL NETWORK FOR ACCURATE FUNCTION APPROXIMATION
Journal of Machine Learning for Modeling and Computing·2025· 1 citedOpen Access
Deep learning for model correction of dynamical systems with data scarcity
arXiv (Cornell University)·2024Open Access
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems
arXiv (Cornell University)·2024· 2 citedOpen Access
Chebyshev Feature Neural Network for Accurate Function Approximation
arXiv (Cornell University)·2024Open Access
Data-driven Effective Modeling of Multiscale Stochastic Dynamical Systems
arXiv (Cornell University)·2024Open Access
Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems
arXiv (Cornell University)·2024Open Access
Modeling Unknown Stochastic Dynamical System Subject to External Excitation
arXiv (Cornell University)·2024Open Access
Unraveling Consumer Purchase Journey Using Neural Network Models
arXiv (Cornell University)·2024Open Access
Learning stochastic dynamical system via flow map operator
Journal of Computational Physics·2024· 15 cited
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Frequent Co-authors

George Em Karniadakis(10), John Jakeman(6), Kailiang Wu(4), Akil Narayan(4), Tong Qin(3), Xueyu Zhu(3), Daniel M. Tartakovsky(2), Jing Li(2), Liang Yan(2), Claude Jeffrey Gittelson(2), Jie Shen(2), Yeonjong Shin(2), Richard Archibald(2), Zhen Chen(2), Jan S. Hesthaven(1), Youssef Marzouk(1), Didier Lucor(1), Chun‐Hsu Su(1), Jia Li(1), Ling Guo(1)