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ORCIDAndrew J. Majda
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- affiliation: New York University, USA
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2020 – today
- 2020
[j42]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)- [j41]M. Nicholas J. Moore, C. Tyler Bolles, Andrew J. Majda, Di Qi:
Anomalous Waves Triggered by Abrupt Depth Changes: Laboratory Experiments and Truncated KdV Statistical Mechanics. J. Nonlinear Sci. 30(6): 3235-3263 (2020)
2010 – 2019
- 2019
- [j40]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) - [j39]Di Qi, Andrew J. Majda:
Transient Metastability and Selective Decay for the Coherent Zonal Structures in Plasma Drift Wave Turbulence. J. Nonlinear Sci. 29(5): 2297-2339 (2019) - 2018
- [j38]Nan Chen, Andrew J. Majda:
Conditional Gaussian Systems for Multiscale Nonlinear Stochastic Systems: Prediction, State Estimation and Uncertainty Quantification. Entropy 20(7): 509 (2018) - [j37]Andrew J. Majda, Nan Chen:
Model Error, Information Barriers, State Estimation and Prediction in Complex Multiscale Systems. Entropy 20(9): 644 (2018) - [j36]Nan Chen, Andrew J. Majda:
Efficient statistically accurate algorithms for the Fokker-Planck equation in large dimensions. J. Comput. Phys. 354: 242-268 (2018) - [j35]Di Qi, Andrew J. Majda:
Rigorous Statistical Bounds in Uncertainty Quantification for One-Layer Turbulent Geophysical Flows. J. Nonlinear Sci. 28(5): 1709-1761 (2018) - [j34]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) - [j33]Michal Branicki, Andrew J. Majda, Kody J. H. Law:
Accuracy of Some Approximate Gaussian Filters for the Navier-Stokes Equation in the Presence of Model Error. Multiscale Model. Simul. 16(4): 1756-1794 (2018) - [j32]Andrew J. Majda, Di Qi:
Strategies for Reduced-Order Models for Predicting the Statistical Responses and Uncertainty Quantification in Complex Turbulent Dynamical Systems. SIAM Rev. 60(3): 491-549 (2018) - 2017
- [j31]Yoonsang Lee, Andrew J. Majda, Di Qi:
Stochastic Superparameterization and Multiscale Filtering of Turbulent Tracers. Multiscale Model. Simul. 15(1): 215-234 (2017) - 2016
- [j30]Noah D. Brenowitz, Dimitrios Giannakis, Andrew J. Majda:
Nonlinear Laplacian spectral analysis of Rayleigh-Bénard convection. J. Comput. Phys. 315: 536-553 (2016) - [j29]Andrew J. Majda, Di Qi:
Improving Prediction Skill of Imperfect Turbulent Models Through Statistical Response and Information Theory. J. Nonlinear Sci. 26(1): 233-285 (2016) - [j28]Andrew J. Majda, Xin T. Tong:
Ergodicity of Truncated Stochastic Navier Stokes with Deterministic Forcing and Dispersion. J. Nonlinear Sci. 26(5): 1483-1506 (2016) - 2015
- [j27]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) - [j26]Michal Branicki, Andrew J. Majda:
An Information-Theoretic Framework for Improving Imperfect Dynamical Predictions Via Multi-Model Ensemble Forecasts. J. Nonlinear Sci. 25(3): 489-538 (2015) - [j25]Yoonsang Lee, Andrew J. Majda:
Multiscale Methods for Data Assimilation in Turbulent Systems. Multiscale Model. Simul. 13(2): 691-713 (2015) - [j24]Ian G. Grooms, Yoonsang Lee, Andrew J. Majda:
Numerical Schemes for Stochastic Backscatter in the Inverse Cascade of Quasigeostrophic Turbulence. Multiscale Model. Simul. 13(3): 1001-1021 (2015) - 2014
- [j23]John Harlim, Adam Mahdi, Andrew J. Majda:
An ensemble Kalman filter for statistical estimation of physics constrained nonlinear regression models. J. Comput. Phys. 257: 782-812 (2014) - [j22]Andrew J. Majda, Ian G. Grooms:
New perspectives on superparameterization for geophysical turbulence. J. Comput. Phys. 271: 60-77 (2014) - [j21]Ian G. Grooms, Andrew J. Majda:
Stochastic superparameterization in quasigeostrophic turbulence. J. Comput. Phys. 271: 78-98 (2014) - [j20]Ian G. Grooms, Yoonsang Lee, Andrew J. Majda:
Ensemble Kalman filters for dynamical systems with unresolved turbulence. J. Comput. Phys. 273: 435-452 (2014) - [j19]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) - [j18]Michèle De La Chevrotière, Boualem Khouider, Andrew J. Majda:
Calibration of the Stochastic Multicloud Model Using Bayesian Inference. SIAM J. Sci. Comput. 36(3) (2014) - 2013
- [j17]Michal Branicki, Andrew J. Majda:
Dynamic Stochastic Superresolution of sparsely observed turbulent systems. J. Comput. Phys. 241: 333-363 (2013) - [j16]Themistoklis P. Sapsis, Andrew J. Majda:
Blending Modified Gaussian Closure and Non-Gaussian Reduced Subspace Methods for Turbulent Dynamical Systems. J. Nonlinear Sci. 23(6): 1039-1071 (2013) - [j15]John Harlim, Andrew J. Majda:
Test Models for Filtering with Superparameterization. Multiscale Model. Simul. 11(1): 282-308 (2013) - [j14]Dimitrios Giannakis, Andrew J. Majda:
Nonlinear Laplacian spectral analysis: capturing intermittent and low-frequency spatiotemporal patterns in high-dimensional data. Stat. Anal. Data Min. 6(3): 180-194 (2013) - 2012
- [j13]Michal Branicki, Boris Gershgorin, Andrew J. Majda:
Filtering skill for turbulent signals for a suite of nonlinear and linear extended Kalman filters. J. Comput. Phys. 231(4): 1462-1498 (2012) - [c2]Dimitrios Giannakis, Wen-wen Tung, Andrew J. Majda:
Hierarchical structure of the Madden-Julian oscillation in infrared brightness temperature revealed through nonlinear Laplacian spectral analysis. CIDU 2012: 55-62 - [i1]Dimitrios Giannakis, Andrew J. Majda:
Nonlinear Laplacian spectral analysis: Capturing intermittent and low-frequency spatiotemporal patterns in high-dimensional data. CoRR abs/1202.6103 (2012) - 2011
- [j12]Boris Gershgorin, Andrew J. Majda:
Filtering a statistically exactly solvable test model for turbulent tracers from partial observations. J. Comput. Phys. 230(4): 1602-1638 (2011) - [c1]Dimitrios Giannakis, Andrew J. Majda:
Time Series Reconstruction via Machine Learning: Revealing Decadal Variability and Intermittency in the North Pacific Sector of a Coupled Climate Model. CIDU 2011: 107-117 - 2010
- [j11]Boris Gershgorin, John Harlim, Andrew J. Majda:
Test models for improving filtering with model errors through stochastic parameter estimation. J. Comput. Phys. 229(1): 1-31 (2010) - [j10]Boris Gershgorin, John Harlim, Andrew J. Majda:
Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation. J. Comput. Phys. 229(1): 32-57 (2010)
2000 – 2009
- 2008
- [j9]Emilio Castronovo, John Harlim, Andrew J. Majda:
Mathematical test criteria for filtering complex systems: Plentiful observations. J. Comput. Phys. 227(7): 3678-3714 (2008) - [j8]John Harlim, Andrew J. Majda:
Mathematical strategies for filtering complex systems: Regularly spaced sparse observations. J. Comput. Phys. 227(10): 5304-5341 (2008) - [j7]Rafail V. Abramov, Andrew J. Majda:
New Approximations and Tests of Linear Fluctuation-Response for Chaotic Nonlinear Forced-Dissipative Dynamical Systems. J. Nonlinear Sci. 18(3): 303-341 (2008) - 2004
- [j6]Andrew J. Majda, Peter R. Kramer:
Stochastic Mode Reduction for the Immersed Boundary Method. SIAM J. Appl. Math. 64(2): 369-400 (2004) - [j5]Andrew J. Majda, Peter R. Kramer:
Stochastic Mode Reduction for Particle-Based Simulation Methods for Complex Microfluid Systems. SIAM J. Appl. Math. 64(2): 401-422 (2004) - [j4]Rafail V. Abramov, Andrew J. Majda:
Quantifying Uncertainty for Non-Gaussian Ensembles in Complex Systems. SIAM J. Sci. Comput. 26(2): 411-447 (2004) - 2002
- [j3]Andrew J. Majda, D. W. McLaughlin, Roy H. Goodman:
Modulations in the Leading Edges of Midlatitude Storm Tracks. SIAM J. Appl. Math. 62(3): 746-776 (2002)
1990 – 1999
- 1991
- [j2]Andrew J. Majda:
Vorticity, Turbulence, and Acoustics in Fluid Flow. SIAM Rev. 33(3): 349-388 (1991) - 1990
- [j1]Andrew J. Majda, Victor Roytburd:
Numerical Study of the Mechanisms for Initiation of Reacting Shock Waves. SIAM J. Sci. Comput. 11(5): 950-974 (1990)
Coauthor Index
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