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Nan Chen 0004
Person information
- affiliation: University of Wisconsin-Madison, Madison, WI, USA
- affiliation (PhD 2016): New York University, Courant Institute of Mathematical Sciences, NY, USA
Other persons with the same name
- Nan Chen — disambiguation page
- Nan Chen 0001 — Southeast University, School of Mechanical Engineering, Vehicle Engineering Laboratory, Nanjing, China (and 2 more)
- Nan Chen 0002
— National University of Singapore, Department of Industrial Systems Engineering and Management, Singapore (and 1 more)
- Nan Chen 0003
— Kunming Institute of Physics, China (and 1 more)
- Nan Chen 0005
— Northwestern Polytechnical University, School of Computer Science and Engineering, Xi'an, China
- Nan Chen 0006
— Tennessee Technological University, USA (and 1 more)
- Nan Chen 0007
— Xidian University, State Key Laboratory of Integrated Services Networks, Xi'an, China
- Nan Chen 0008 — Zhejiang University, School of Computer Science and Technology, Hangzhou, China
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2020 – today
- 2024
- [j12]Chuanqi Chen, Nan Chen
, Jinlong Wu
:
CGNSDE: Conditional Gaussian neural stochastic differential equation for modeling complex systems and data assimilation. Comput. Phys. Commun. 304: 109302 (2024) - [i3]Chuanqi Chen, Nan Chen, Jinlong Wu:
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation. CoRR abs/2404.06749 (2024) - 2023
- [j11]Changhong Mou, Nan Chen
, Traian Iliescu:
An efficient data-driven multiscale stochastic reduced order modeling framework for complex systems. J. Comput. Phys. 493: 112450 (2023) - [i2]Chuanqi Chen, Nan Chen, Jinlong Wu:
CEBoosting: Online Sparse Identification of Dynamical Systems with Regime Switching by Causation Entropy Boosting. CoRR abs/2304.07863 (2023) - 2022
- [i1]Changhong Mou, Nan Chen, Traian Iliescu:
An Efficient Data-Driven Multiscale Stochastic Reduced Order Modeling Framework for Complex Systems. CoRR abs/2203.11438 (2022) - 2020
- [j10]Nan Chen:
Can Short and Partial Observations Reduce Model Error and Facilitate Machine Learning Prediction? Entropy 22(10): 1075 (2020) - [j9]Nan Chen
, Andrew J. Majda:
Efficient nonlinear optimal smoothing and sampling algorithms for complex turbulent nonlinear dynamical systems with partial observations. J. Comput. Phys. 410: 109381 (2020) - [j8]Nan Chen
:
Learning nonlinear turbulent dynamics from partial observations via analytically solvable conditional statistics. J. Comput. Phys. 418: 109635 (2020)
2010 – 2019
- 2019
- [j7]Nan Chen
, Andrew J. Majda:
A new efficient parameter estimation algorithm for high-dimensional complex nonlinear turbulent dynamical systems with partial observations. J. Comput. Phys. 397 (2019) - 2018
- [j6]Nan Chen, Andrew J. Majda:
Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification. Entropy 20(7): 509 (2018) - [j5]Andrew J. Majda, Nan Chen:
Model Error, Information Barriers, State Estimation and Prediction in Complex Multiscale Systems. Entropy 20(9): 644 (2018) - [j4]Nan Chen
, Andrew J. Majda:
Efficient statistically accurate algorithms for the Fokker-Planck equation in large dimensions. J. Comput. Phys. 354: 242-268 (2018) - [j3]Nan Chen
, Andrew J. Majda, Xin T. Tong
:
Rigorous Analysis for Efficient Statistically Accurate Algorithms for Solving Fokker-Planck Equations in Large Dimensions. SIAM/ASA J. Uncertain. Quantification 6(3): 1198-1223 (2018) - 2015
- [j2]Nan Chen, Andrew J. Majda, Xin T. Tong
:
Noisy Lagrangian Tracers for Filtering Random Rotating Compressible Flows. J. Nonlinear Sci. 25(3): 451-488 (2015) - 2014
- [j1]Nan Chen, Dimitrios Giannakis
, Radu Herbei, Andrew J. Majda:
An MCMC Algorithm for Parameter Estimation in Signals with Hidden Intermittent Instability. SIAM/ASA J. Uncertain. Quantification 2(1): 647-669 (2014)
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last updated on 2024-08-27 22:01 CEST by the dblp team
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