Hassan Arbabi
Hassan Arbabi
Data Scientist @ Safekeep
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Cited by
Cited by
Ergodic theory, dynamic mode decomposition, and computation of spectral properties of the Koopman operator
H Arbabi, I Mezic
SIAM Journal on Applied Dynamical Systems 16 (4), 2096-2126, 2017
A data-driven koopman model predictive control framework for nonlinear partial differential equations
H Arbabi, M Korda, I Mezić
2018 IEEE Conference on Decision and Control (CDC), 6409-6414, 2018
Study of dynamics in post-transient flows using Koopman mode decomposition
H Arbabi, I Mezić
Physical Review Fluids 2 (12), 124402, 2017
Linking machine learning with multiscale numerics: data-driven discovery of homogenized equations
H Arbabi, JE Bunder, G Samaey, AJ Roberts, IG Kevrekidis
Jom 72 (12), 4444-4457, 2020
Introduction to Koopman operator theory of dynamical systems
H Arbabi
Introduction to Koopman operator theory of dynamical systems, 2018
Generative stochastic modeling of strongly nonlinear flows with non-Gaussian statistics
H Arbabi, T Sapsis
SIAM/ASA Journal on Uncertainty Quantification 10 (2), 555-583, 2022
Search strategy in a complex and dynamic environment: The MH370 case
S Ivić, B Crnković, H Arbabi, S Loire, P Clary, I Mezić
Scientific reports 10 (1), 1-15, 2020
An operator-theoretic viewpoint to non-smooth dynamical systems: Koopman analysis of a hybrid pendulum
N Govindarajan, H Arbabi, L Van Blargian, T Matchen, E Tegling
2016 IEEE 55th Conference on Decision and Control (CDC), 6477-6484, 2016
On the Computation of Isostables, Isochrons and Other Spectral Objects of the Koopman Operator Using the Dynamic Mode Decomposition
I Mezic, H Arbabi
International Symposium on Nonlinear Theory and Its Applications, 2017
Particles to partial differential equations parsimoniously<? A3B2 show [editpick]?>
H Arbabi, IG Kevrekidis
Chaos: An Interdisciplinary Journal of Nonlinear Science 31 (3), 033137, 2021
Prandtl–Batchelor theorem for flows with quasiperiodic time dependence
H Arbabi, I Mezić
Journal of Fluid Mechanics 862, 2019
Computation of transient koopman spectrum using hankel-dynamic mode decompoisition
H Arbabi, I Mezic
APS Division of Fluid Dynamics Meeting Abstracts, G1. 009, 2017
Koopman spectral analysis and study of mixing in incompressible flows
H Arbabi
University of California, Santa Barbara, 2017
Coarse-grained and emergent distributed parameter systems from data
H Arbabi, FP Kemeth, T Bertalan, I Kevrekidis
2021 American Control Conference (ACC), 4063-4068, 2021
Spectral analysis of mixing in 2D high-Reynolds flows
H Arbabi, I Mezic
arXiv preprint arXiv:1903.10044, 2019
Mean Subtraction and Mode Selection in Dynamic Mode Decomposition
GS Seenivasaharagavan, M Korda, H Arbabi, I Mezić
arXiv preprint arXiv:2105.03607, 2021
Learning Coarse-Grained Partial Differential Equations from Fine-Scale Data Via Machine Learning
S Lee, G Psarellis, H Arbabi, C Siettos, F Dietrich, G Samaey, ...
2020 Virtual AIChE Annual Meeting, 2020
Dynamical-Systems-Guided Learning of PDEs from Data
H Arbabi, T Bertalan, A Roberts, G Samaey, IG Kevrekidis
2020 Virtual AIChE Annual Meeting, 2020
Data-driven modeling of chaotic flows with non-Gaussian statistics
H Arbabi, T Sapsis
APS Division of Fluid Dynamics Meeting Abstracts, P10. 004, 2019
Koopman mode representations of vortex interactions and instabilities
S Sadri, H Arbabi, I Mezic, P Luzzatto Fegiz
Bulletin of the American Physical Society 63, 2018
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