A-Z 索引
Xiu, Dongbin
Professor and Ohio Eminent Scholar
dxiu@purdue.edu; dxiu@sci.utah.edu; xiu.16@osu.edu
https://people.math.osu.edu/xiu.16/（在新标签页中打开）
Department of Mathematics, The Ohio State University, Columbus, 43210 Ohio,
USA
Department of mathematics Ohio State University, Columbus, OH, UNITED STATES, 43210
https://www.osu.edu/（在新标签页中打开）
Journals:
International Journal for Uncertainty Quantification（在新标签页中打开）
Articles:
FAST METHOD FOR HIGH-FREQUENCY ACOUSTIC SCATTERING FROM RANDOM SCATTERERS（在新标签页中打开） - Vol. 1 '2011（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
DEEP LEARNING OF PARAMETERIZED EQUATIONS WITH APPLICATIONS TO UNCERTAINTY QUANTIFICATION（在新标签页中打开） - Vol. 11 '2021（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH（在新标签页中打开） - Vol. 14 '2024（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS （在新标签页中打开） - Vol. 2 '2012（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
STOCHASTIC COLLOCATION ALGORITHMS USING 𝓁1-MINIMIZATION（在新标签页中打开） - Vol. 2 '2012（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
VISUALIZATION OF COVARIANCE AND CROSS-COVARIANCE FIELDS（在新标签页中打开） - Vol. 3 '2013（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
PREFACE: FIRST QUEST CONFERENCE（在新标签页中打开） - Vol. 6 '2016（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
UNCERTAINTY QUANTIFICATION OF SCIENTIFIC PROPOSAL EVALUATIONS（在新标签页中打开） - Vol. 6 '2016（在新标签页中打开） - International Journal for Uncertainty Quantification（在新标签页中打开）
LEARNING REDUCED SYSTEMS VIA DEEP NEURAL NETWORKS WITH MEMORY（在新标签页中打开） - Vol. 1 '2020（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
DEEP LEARNING OF CHAOTIC SYSTEMS FROM PARTIALLY-OBSERVED DATA（在新标签页中打开） - Vol. 3 '2022（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
LEARNING FINE SCALE DYNAMICS FROM COARSE OBSERVATIONS VIA INNER RECURRENCE（在新标签页中打开） - Vol. 3 '2022（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
MODELING UNKNOWN DYNAMICAL SYSTEMS WITH HIDDEN PARAMETERS（在新标签页中打开） - Vol. 3 '2022（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
FLOW MAP LEARNING FOR UNKNOWN DYNAMICAL SYSTEMS: OVERVIEW, IMPLEMENTATION, AND BENCHMARKS（在新标签页中打开） - Vol. 4 '2023（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
MODELING UNKNOWN STOCHASTIC DYNAMICAL SYSTEM VIA AUTOENCODER（在新标签页中打开） - Vol. 5 '2024（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
UNRAVELING CONSUMER PURCHASE JOURNEY USING NEURAL NETWORK MODELS（在新标签页中打开） - Vol. 5 '2024（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
CHEBYSHEV FEATURE NEURAL NETWORK FOR ACCURATE FUNCTION APPROXIMATION（在新标签页中打开） - Vol. 6 '2025（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
DIMENSION-REDUCED RECONSTRUCTION MAP LEARNING FOR PARAMETER ESTIMATION IN LIKELIHOOD-FREE INFERENCE PROBLEMS（在新标签页中打开） - Vol. 6 '2025（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
LEARNING INVERSE MAPS FOR PARAMETER ESTIMATION IN DYNAMICAL SYSTEMS（在新标签页中打开） - Vol. 7 '2026（在新标签页中打开） - Journal of Machine Learning for Modeling and Computing（在新标签页中打开）
Qin, Tong
DEEP LEARNING OF PARAMETERIZED EQUATIONS WITH APPLICATIONS TO UNCERTAINTY QUANTIFICATION
Chen, Zhen
DEEP LEARNING OF PARAMETERIZED EQUATIONS WITH APPLICATIONS TO UNCERTAINTY QUANTIFICATION
Churchill, Victor
LEARNING INVERSE MAPS FOR PARAMETER ESTIMATION IN DYNAMICAL SYSTEMS
UNRAVELING CONSUMER PURCHASE JOURNEY USING NEURAL NETWORK MODELS
DEEP LEARNING OF CHAOTIC SYSTEMS FROM PARTIALLY-OBSERVED DATA
FLOW MAP LEARNING FOR UNKNOWN DYNAMICAL SYSTEMS: OVERVIEW, IMPLEMENTATION, AND BENCHMARKS
LEARNING FINE SCALE DYNAMICS FROM COARSE OBSERVATIONS VIA INNER RECURRENCE
Taghizadeh, Mehdi
IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH
Wang, Peng
UNCERTAINTY QUANTIFICATION OF SCIENTIFIC PROPOSAL EVALUATIONS
PREFACE: FIRST QUEST CONFERENCE
Tatsuoka, Caroline
LEARNING INVERSE MAPS FOR PARAMETER ESTIMATION IN DYNAMICAL SYSTEMS
Guo, Ling
STOCHASTIC COLLOCATION ALGORITHMS USING 𝓁1-MINIMIZATION
Jakeman, John D.
DEEP LEARNING OF PARAMETERIZED EQUATIONS WITH APPLICATIONS TO UNCERTAINTY QUANTIFICATION
Zhang, Rui
DIMENSION-REDUCED RECONSTRUCTION MAP LEARNING FOR PARAMETER ESTIMATION IN LIKELIHOOD-FREE INFERENCE PROBLEMS
Chang, Lo-Bin
LEARNING REDUCED SYSTEMS VIA DEEP NEURAL NETWORKS WITH MEMORY
MODELING UNKNOWN DYNAMICAL SYSTEMS WITH HIDDEN PARAMETERS
Alemazkoor, Negin
IMPROVING ACCURACY AND COMPUTATIONAL EFFICIENCY OF OPTIMAL DESIGN OF EXPERIMENTS VIA GREEDY BACKWARD APPROACH
Chen, Qifan
MODELING UNKNOWN STOCHASTIC DYNAMICAL SYSTEM VIA AUTOENCODER
Xu, Zhongshu
LEARNING INVERSE MAPS FOR PARAMETER ESTIMATION IN DYNAMICAL SYSTEMS
CHEBYSHEV FEATURE NEURAL NETWORK FOR ACCURATE FUNCTION APPROXIMATION
MODELING UNKNOWN STOCHASTIC DYNAMICAL SYSTEM VIA AUTOENCODER
Tartakovsky, Daniel M.
COMPUTATIONAL FRAMEWORK FOR REAL-TIME DIGITAL TWINS
PREFACE: FIRST QUEST CONFERENCE
Chen, Yuan
CHEBYSHEV FEATURE NEURAL NETWORK FOR ACCURATE FUNCTION APPROXIMATION
MODELING UNKNOWN STOCHASTIC DYNAMICAL SYSTEM VIA AUTOENCODER
Mao, WeiZe
MODELING UNKNOWN DYNAMICAL SYSTEMS WITH HIDDEN PARAMETERS
Potter, Kristin
INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS
Kirby, Robert Mike
VISUALIZATION OF COVARIANCE AND CROSS-COVARIANCE FIELDS
INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS
Yang, Chao
VISUALIZATION OF COVARIANCE AND CROSS-COVARIANCE FIELDS
Shi, Xiaofeng
UNCERTAINTY QUANTIFICATION OF SCIENTIFIC PROPOSAL EVALUATIONS
Chkrebtii, Oksana
DIMENSION-REDUCED RECONSTRUCTION MAP LEARNING FOR PARAMETER ESTIMATION IN LIKELIHOOD-FREE INFERENCE PROBLEMS
Tsuji, Paul
FAST METHOD FOR HIGH-FREQUENCY ACOUSTIC SCATTERING FROM RANDOM SCATTERERS
Yan, Liang
STOCHASTIC COLLOCATION ALGORITHMS USING 𝓁1-MINIMIZATION
Fu, Xiaohan
LEARNING REDUCED SYSTEMS VIA DEEP NEURAL NETWORKS WITH MEMORY
MODELING UNKNOWN DYNAMICAL SYSTEMS WITH HIDDEN PARAMETERS
Li, H. Alice
UNRAVELING CONSUMER PURCHASE JOURNEY USING NEURAL NETWORK MODELS
Johnson, Chris R.
INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS
Ying, Lexing
FAST METHOD FOR HIGH-FREQUENCY ACOUSTIC SCATTERING FROM RANDOM SCATTERERS