| Feasibility analysis of ensemble sensitivity computation in turbulent flows N Chandramoorthy, P Fernandez, C Talnikar, Q Wang AIAA Journal 57 (10), 4514-4526, 2019 | 54* | 2019 |
| On the probability of finding nonphysical solutions through shadowing N Chandramoorthy, Q Wang Journal of Computational Physics 440, 110389, 2021 | 26 | 2021 |
| A computable realization of Ruelle's formula for linear response of statistics in chaotic systems N Chandramoorthy, Q Wang arXiv preprint arXiv:2002.04117, 2020 | 21 | 2020 |
| On the generalization of learning algorithms that do not converge N Chandramoorthy, A Loukas, K Gatmiry, S Jegelka NeurIPS 2022, 2022 | 15 | 2022 |
| Ergodic sensitivity analysis of one-dimensional chaotic maps AA Śliwiak, N Chandramoorthy, Q Wang Theoretical and Applied Mechanics Letters 10 (6), 438-447, 2020 | 15 | 2020 |
| Efficient computation of linear response of chaotic attractors with one-dimensional unstable manifolds N Chandramoorthy, Q Wang SIAM Journal on Applied Dynamical Systems 21 (2), 735-781, 2022 | 13 | 2022 |
| Computational assessment of smooth and rough parameter dependence of statistics in chaotic dynamical systems AA Śliwiak, N Chandramoorthy, Q Wang Communications in Nonlinear Science and Numerical Simulation 101, 105906, 2021 | 12 | 2021 |
| Toward computing sensitivities of average quantities in turbulent flows N Chandramoorthy, ZN Wang, Q Wang, P Tucker arXiv preprint arXiv:1902.11112, 2019 | 11 | 2019 |
| Rigorous justification for the space–split sensitivity algorithm to compute linear response in Anosov systems N Chandramoorthy, M Jézéquel Nonlinearity 35 (8), 4357, 2022 | 10 | 2022 |
| An ergodic-averaging method to differentiate covariant Lyapunov vectors: Computing the curvature of one-dimensional unstable manifolds of strange attractors N Chandramoorthy, Q Wang Nonlinear Dynamics 104, 4083-4102, 2021 | 9 | 2021 |
| Variational optimization and data assimilation in chaotic time-delayed systems with automatic-differentiated shadowing sensitivity N Chandramoorthy, L Magri, Q Wang arXiv preprint arXiv:2011.08794, 2020 | 9 | 2020 |
| Sensitivity computation of statistically stationary quantities in turbulent flows N Chandramoorthy, Q Wang AIAA Aviation 2019 Forum, 3426, 2019 | 7 | 2019 |
| Solving lubrication problems at the nanometer scale N Chandramoorthy, NG Hadjiconstantinou Microfluidics and Nanofluidics 22, 1-12, 2018 | 6 | 2018 |
| Algorithmic differentiation of shadowing sensitivities in chaotic systems N Chandramoorthy, Q Wang, L Magri, SHK Narayanan, P Hovland, A Ni SIAM Workshop on Combinatorial Scientific Computing, 1-18, 2018 | 6 | 2018 |
| An efficient algorithm for sensitivity analysis of chaotic systems N Chandramoorthy Massachusetts Institute of Technology, 2021 | 5 | 2021 |
| A Reynolds lubrication equation for dense fluids valid beyond Navier-Stokes N Chandramoorthy, N Hadjiconstantinou APS Division of Fluid Dynamics Meeting Abstracts, E22. 001, 2016 | 4 | 2016 |
| When are dynamical systems learned from time series data statistically accurate? J Park, N Yang, N Chandramoorthy NeurIPS 2024, 2024 | 3 | 2024 |
| Molecular dynamics-based approaches for mesoscale lubrication N Chandramoorthy Massachusetts Institute of Technology, 2016 | 2 | 2016 |
| Sensitivity analysis of hydrodynamic chaos in combustion using NILSS-AD N Chandramoorthy, Q Wang, L Magri, SHK Narayanan, P Hovland APS Division of Fluid Dynamics Meeting Abstracts, Q1. 001, 2017 | 1 | 2017 |
| Score Operator Newton transport N Chandramoorthy, FT Schaefer, YM Marzouk International Conference on Artificial Intelligence and Statistics, 3349-3357, 2024 | | 2024 |
Qiqi WangAssociate Professor of Aeronautics and Astronautics, MITPatvirtintas el. paštas mit.edu
