Dongbin Xiu - RankMe

100 papers Misc 1Journal 99

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Modeling Unknown Stochastic Dynamical System Subject to External Excitation. SIAM J. Sci. Comput. Yuan Chen, Dongbin Xiu
2026	J	`jnl`	Numerical Approach for On-the-Fly Active Flow Control via Flow Map Learning Method. CoRR Xinyu Liu, Qifan Chen, Dongbin Xiu
2025	J	`jnl`	A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems. SIAM J. Sci. Comput. Yanfang Liu, Yuan Chen, Dongbin Xiu, Guannan Zhang
2025	J	`jnl`	DUE: A Deep Learning Framework and Library for Modeling Unknown Equations. CoRR Junfeng Chen, Kailiang Wu, Dongbin Xiu
2025	J	`jnl`	DUE: A Deep Learning Framework and Library for Modeling Unknown Equations. SIAM Rev. Junfeng Chen, Kailiang Wu, Dongbin Xiu
2025	J	`jnl`	Deep Learning for Model Correction of Dynamical Systems with Data Scarcity. SIAM/ASA J. Uncertain. Quantification Caroline Tatsuoka, Dongbin Xiu
2025	J	`jnl`	Exact Conditional Score-Guided Generative Modeling for Amortized Inference in Uncertainty Quantification. CoRR Zezhong Zhang, Caroline Tatsuoka, Dongbin Xiu, Guannan Zhang
2025	J	`jnl`	Multi-fidelity Parameter Estimation Using Conditional Diffusion Models. CoRR Caroline Tatsuoka, Minglei Yang, Dongbin Xiu, Guannan Zhang
2025	J	`jnl`	On Enforcing Nonnegativity in Polynomial Approximations in High Dimensions. SIAM J. Sci. Comput. Yuan Chen, Dongbin Xiu, Xiangxiong Zhang
2025	J	`jnl`	Targeted Digital Twin via Flow Map Learning and Its Application to Fluid Dynamics. CoRR Qifan Chen, Zhongshu Xu, Jinjin Zhang, Dongbin Xiu
2024	J	`jnl`	A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical Systems. CoRR Yanfang Liu, Yuan Chen, Dongbin Xiu, Guannan Zhang
2024	J	`jnl`	Chebyshev Feature Neural Network for Accurate Function Approximation. CoRR Zhongshu Xu, Yuan Chen, Dongbin Xiu
2024	J	`jnl`	Data-driven Effective Modeling of Multiscale Stochastic Dynamical Systems. CoRR Yuan Chen, Dongbin Xiu
2024	J	`jnl`	Deep learning for model correction of dynamical systems with data scarcity. CoRR Caroline Tatsuoka, Dongbin Xiu
2024	J	`jnl`	Learning stochastic dynamical system via flow map operator. J. Comput. Phys. Yuan Chen, Dongbin Xiu
2024	J	`jnl`	Modeling Unknown Stochastic Dynamical System Subject to External Excitation. CoRR Yuan Chen, Dongbin Xiu
2024	J	`jnl`	On enforcing non-negativity in polynomial approximations in high dimensions. CoRR Yuan Chen, Dongbin Xiu, Xiangxiong Zhang
2023	J	`jnl`	DNN modeling of partial differential equations with incomplete data. J. Comput. Phys. Victor Churchill, Yuan Chen, Zhongshu Xu, Dongbin Xiu
2023	J	`jnl`	Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and Benchmarks. CoRR Victor Churchill, Dongbin Xiu
2023	J	`jnl`	Learning Stochastic Dynamical System via Flow Map Operator. CoRR Yuan Chen, Dongbin Xiu
2023	J	`jnl`	Modeling Unknown Stochastic Dynamical System via Autoencoder. CoRR Zhongshu Xu, Yuan Chen, Qifan Chen, Dongbin Xiu
2023	J	`jnl`	Robust modeling of unknown dynamical systems via ensemble averaged learning. J. Comput. Phys. Victor Churchill, Steve Manns, Zhen Chen, Dongbin Xiu
2022	J	`jnl`	Construction of discontinuity detectors using convolutional neural networks. J. Sci. Comput. Shuyi Wang, Zixu Zhou, Lo-Bin Chang, Dongbin Xiu
2022	J	`jnl`	Deep Learning of Chaotic Systems from Partially-Observed Data. CoRR Victor Churchill, Dongbin Xiu
2022	J	`jnl`	Deep neural network modeling of unknown partial differential equations in nodal space. J. Comput. Phys. Zhen Chen, Victor Churchill, Kailiang Wu, Dongbin Xiu
2022	J	`jnl`	Learning Fine Scale Dynamics from Coarse Observations via Inner Recurrence. CoRR Victor Churchill, Dongbin Xiu
2022	J	`jnl`	Modeling unknown dynamical systems with hidden parameters. CoRR Xiaohan Fu, Weize Mao, Lo-Bin Chang, Dongbin Xiu
2022	J	`jnl`	Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged Learning. CoRR Victor Churchill, Steve Manns, Zhen Chen, Dongbin Xiu
2021	J	`jnl`	Data-Driven Learning of Nonautonomous Systems. SIAM J. Sci. Comput. Tong Qin, Zhen Chen, John D. Jakeman, Dongbin Xiu
2021	J	`jnl`	Deep Neural Network Modeling of Unknown Partial Differential Equations in Nodal Space. CoRR Zhen Chen, Victor Churchill, Kailiang Wu, Dongbin Xiu
2021	J	`jnl`	On generalized residual network for deep learning of unknown dynamical systems. J. Comput. Phys. Zhen Chen, Dongbin Xiu
2020	J	`jnl`	A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data. CoRR Jun Hou, Tong Qin, Kailiang Wu, Dongbin Xiu
2020	J	`jnl`	Data-driven deep learning of partial differential equations in modal space. J. Comput. Phys. Kailiang Wu, Dongbin Xiu
2020	J	`jnl`	Data-driven learning of non-autonomous systems. CoRR Tong Qin, Zhen Chen, John D. Jakeman, Dongbin Xiu
2020	J	`jnl`	Learning reduced systems via deep neural networks with memory. CoRR Xiaohan Fu, Lo-Bin Chang, Dongbin Xiu
2020	J	`jnl`	Methods to Recover Unknown Processes in Partial Differential Equations Using Data. CoRR Zhen Chen, Kailiang Wu, Dongbin Xiu
2020	J	`jnl`	Methods to Recover Unknown Processes in Partial Differential Equations Using Data. J. Sci. Comput. Zhen Chen, Kailiang Wu, Dongbin Xiu
2020	J	`jnl`	On generalized residue network for deep learning of unknown dynamical systems. CoRR Zhen Chen, Dongbin Xiu
2020	J	`jnl`	Structure-Preserving Method for Reconstructing Unknown Hamiltonian Systems From Trajectory Data. SIAM J. Sci. Comput. Kailiang Wu, Tong Qin, Dongbin Xiu
2019	J	`jnl`	A neural network approach for uncertainty quantification for time-dependent problems with random parameters. CoRR Tong Qin, Zhen Chen, John D. Jakeman, Dongbin Xiu
2019	J	`jnl`	Data driven governing equations approximation using deep neural networks. J. Comput. Phys. Tong Qin, Kailiang Wu, Dongbin Xiu
2019	J	`jnl`	Data-Driven Deep Learning of Partial Differential Equations in Modal Space. CoRR Kailiang Wu, Dongbin Xiu
2019	J	`jnl`	Energy conserving Galerkin approximation of two dimensional wave equations with random coefficients. J. Comput. Phys. Ching-Shan Chou, Yukun Li, Dongbin Xiu
2019	J	`jnl`	Numerical aspects for approximating governing equations using data. J. Comput. Phys. Kailiang Wu, Dongbin Xiu
2019	J	`jnl`	Structure-preserving Method for Reconstructing Unknown Hamiltonian Systems from Trajectory Data. CoRR Kailiang Wu, Tong Qin, Dongbin Xiu
2019	J	`jnl`	Uncertainty quantification of discontinuous outputs via a non-intrusive bifidelity strategy. J. Comput. Phys. Claudio Canuto, Sandra Pieraccini, Dongbin Xiu
2018	J	`jnl`	An Explicit Neural Network Construction for Piecewise Constant Function Approximation. CoRR Kailiang Wu, Dongbin Xiu
2018	J	`jnl`	Data Driven Governing Equations Approximation Using Deep Neural Networks. CoRR Tong Qin, Kailiang Wu, Dongbin Xiu
2018	J	`jnl`	Numerical Aspects for Approximating Governing Equations Using Data. CoRR Kailiang Wu, Dongbin Xiu
2018	J	`jnl`	Parameter uncertainty quantification using surrogate models applied to a spatial model of yeast mating polarization. PLoS Comput. Biol. Marissa Renardy, Tau-Mu Yi, Dongbin Xiu, Ching-Shan Chou
2018	J	`jnl`	Reducing Parameter Space for Neural Network Training. CoRR Tong Qin, Ling Zhou, Dongbin Xiu
2018	J	`jnl`	Sequential function approximation on arbitrarily distributed point sets. J. Comput. Phys. Kailiang Wu, Dongbin Xiu
2018	J	`jnl`	Sequential function approximation with noisy data. J. Comput. Phys. Yeonjong Shin, Kailiang Wu, Dongbin Xiu
2017	J	`jnl`	A Randomized Algorithm for Multivariate Function Approximation. SIAM J. Sci. Comput. Yeonjong Shin, Dongbin Xiu
2017	J	`jnl`	A Randomized Tensor Quadrature Method for High Dimensional Polynomial Approximation. SIAM J. Sci. Comput. Kailiang Wu, Yeonjong Shin, Dongbin Xiu
2017	J	`jnl`	A stochastic Galerkin method for first-order quasilinear hyperbolic systems with uncertainty. J. Comput. Phys. Kailiang Wu, Huazhong Tang, Dongbin Xiu
2017	J	`jnl`	Multi-fidelity stochastic collocation method for computation of statistical moments. J. Comput. Phys. Xueyu Zhu, Erin M. Linebarger, Dongbin Xiu
2017	J	`jnl`	Sparse Approximation using ℓ SIAM J. Sci. Comput. Liang Yan, Yeonjong Shin, Dongbin Xiu
2016	J	`jnl`	A Well-Balanced Stochastic Galerkin Method for Scalar Hyperbolic Balance Laws with Random Inputs. J. Sci. Comput. Shi Jin, Dongbin Xiu, Xueyu Zhu
2016	J	`jnl`	Correcting Data Corruption Errors for Multivariate Function Approximation. SIAM J. Sci. Comput. Yeonjong Shin, Dongbin Xiu
2016	J	`jnl`	Nonadaptive Quasi-Optimal Points Selection for Least Squares Linear Regression. SIAM J. Sci. Comput. Yeonjong Shin, Dongbin Xiu
2016	J	`jnl`	Numerical strategy for model correction using physical constraints. J. Comput. Phys. Yanyan He, Dongbin Xiu
2016	J	`jnl`	On a near optimal sampling strategy for least squares polynomial regression. J. Comput. Phys. Yeonjong Shin, Dongbin Xiu
2015	J	`jnl`	A Stochastic Galerkin Method for Hamilton-Jacobi Equations with Uncertainty. SIAM J. Sci. Comput. Jingwei Hu, Shi Jin, Dongbin Xiu
2015	J	`jnl`	An Efficient Method for Uncertainty Propagation using Fuzzy Sets. SIAM J. Sci. Comput. Xiaoxiao Chen, Yanyan He, Dongbin Xiu
2015	J	`jnl`	Asymptotic-preserving methods for hyperbolic and transport equations with random inputs and diffusive scalings. J. Comput. Phys. Shi Jin, Dongbin Xiu, Xueyu Zhu
2015	J	`jnl`	Local Polynomial Chaos Expansion for Linear Differential Equations with High Dimensional Random Inputs. SIAM J. Sci. Comput. Yi Chen, John D. Jakeman, Claude Jeffrey Gittelson, Dongbin Xiu
2015	J	`jnl`	Weighted discrete least-squares polynomial approximation using randomized quadratures. J. Comput. Phys. Tao Zhou, Akil Narayan, Dongbin Xiu
2014	J	`jnl`	A Stochastic Collocation Algorithm with Multifidelity Models. SIAM J. Sci. Comput. Akil Narayan, Claude Jeffrey Gittelson, Dongbin Xiu
2014	J	`jnl`	Computational Aspects of Stochastic Collocation with Multifidelity Models. SIAM/ASA J. Uncertain. Quantification Xueyu Zhu, Akil Narayan, Dongbin Xiu
2014	J	`jnl`	On Upper and Lower Bounds for Quantity of Interest in Problems Subject to Epistemic Uncertainty. SIAM J. Sci. Comput. Jing Li, Xin Qi, Dongbin Xiu
2014	J	`jnl`	Surrogate Based Method for Evaluation of Failure Probability under Multiple Constraints. SIAM J. Sci. Comput. Jing Li, Dongbin Xiu
2013	J	`jnl`	A flexible numerical approach for quantification of epistemic uncertainty. J. Comput. Phys. Xiaoxiao Chen, Eun-Jae Park, Dongbin Xiu
2013	J	`jnl`	Constructing Nested Nodal Sets for Multivariate Polynomial Interpolation. SIAM J. Sci. Comput. Akil Narayan, Dongbin Xiu
2013	J	`jnl`	Minimal multi-element stochastic collocation for uncertainty quantification of discontinuous functions. J. Comput. Phys. John D. Jakeman, Akil Narayan, Dongbin Xiu
2012	J	`jnl`	Computation of Failure Probability Subject to Epistemic Uncertainty. SIAM J. Sci. Comput. Jing Li, Dongbin Xiu
2012	J	`jnl`	Generalised Polynomial Chaos for a Class of Linear Conservation Laws. J. Sci. Comput. Roland Pulch, Dongbin Xiu
2012	J	`jnl`	Sequential data assimilation with multiple models. J. Comput. Phys. Akil Narayan, Youssef M. Marzouk, Dongbin Xiu
2012	J	`jnl`	Stochastic Collocation Methods on Unstructured Grids in High Dimensions via Interpolation. SIAM J. Sci. Comput. Akil Narayan, Dongbin Xiu
2012	J	`jnl`	Stochastic Collocation for Optimal Control Problems with Stochastic PDE Constraints. SIAM J. Control. Optim. Hanne Tiesler, Robert M. Kirby, Dongbin Xiu, Tobias Preusser
2011	J	`jnl`	An efficient surrogate-based method for computing rare failure probability. J. Comput. Phys. Jing Li, Jinglai Li, Dongbin Xiu
2011	J	`jnl`	Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids. J. Comput. Phys. John D. Jakeman, Richard Archibald, Dongbin Xiu
2010	J	`jnl`	Evaluation of failure probability via surrogate models. J. Comput. Phys. Jing Li, Dongbin Xiu
2010	J	`jnl`	Numerical approach for quantification of epistemic uncertainty. J. Comput. Phys. John D. Jakeman, Michael S. Eldred, Dongbin Xiu
2009	J	`jnl`	A generalized polynomial chaos based ensemble Kalman filter with high accuracy. J. Comput. Phys. Jia Li, Dongbin Xiu
2009	J	`jnl`	Discontinuity detection in multivariate space for stochastic simulations. J. Comput. Phys. Rick Archibald, Anne Gelb, Rishu Saxena, Dongbin Xiu
2009	J	`jnl`	Efficient stochastic Galerkin methods for random diffusion equations. J. Comput. Phys. Dongbin Xiu, Jie Shen
2007	J	`jnl`	Guest Editors' Introduction: Stochastic Modeling of Complex Systems. Comput. Sci. Eng. Daniel M. Tartakovsky, Dongbin Xiu
2007	J	`jnl`	Parametric uncertainty analysis of pulse wave propagation in a model of a human arterial network. J. Comput. Phys. Dongbin Xiu, Spencer J. Sherwin
2006	J	`jnl`	Numerical Methods for Differential Equations in Random Domains. SIAM J. Sci. Comput. Dongbin Xiu, Daniel M. Tartakovsky
2006	J	`jnl`	Stochastic analysis of transport in tubes with rough walls. J. Comput. Phys. Daniel M. Tartakovsky, Dongbin Xiu
2005	J	`jnl`	An equation-free, multiscale approach to uncertainty quantification. Comput. Sci. Eng. Dongbin Xiu, Ioannis G. Kevrekidis, Roger G. Ghanem
2005	J	`jnl`	Equation-Free, Multiscale Computation for Unsteady Random Diffusion. Multiscale Model. Simul. Dongbin Xiu, Ioannis G. Kevrekidis
2005	J	`jnl`	High-Order Collocation Methods for Differential Equations with Random Inputs. SIAM J. Sci. Comput. Dongbin Xiu, Jan S. Hesthaven
2005	J	`jnl`	Strong and Auxiliary Forms of the Semi-Lagrangian Method for Incompressible Flows. J. Sci. Comput. Dongbin Xiu, Spencer J. Sherwin, Suchuan Dong, George E. Karniadakis
2004	J	`jnl`	A Two-Scale Nonperturbative Approach to Uncertainty Analysis of Diffusion in Random Composites. Multiscale Model. Simul. Dongbin Xiu, Daniel M. Tartakovsky
2004	J	`jnl`	Stochastic Solutions for the Two-Dimensional Advection-Diffusion Equation. SIAM J. Sci. Comput. Xiaoliang Wan, Dongbin Xiu, George E. Karniadakis
2003	Misc	`conf`	Performance Evaluation of Generalized Polynomial Chaos. International Conference on Computational Science Dongbin Xiu, Didier Lucor, Chau-Hsing Su, George E. Karniadakis
2002	J	`jnl`	A Semi-Lagrangian Method for Turbulence Simulations Using Mixed Spectral Discretizations. J. Sci. Comput. Jin Xu, Dongbin Xiu, George E. Karniadakis
2002	J	`jnl`	The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations. SIAM J. Sci. Comput. Dongbin Xiu, George E. Karniadakis