Numerical Assessment of a Nonintrusive Surrogate Model Based on Recurrent Neural Networks and Proper Orthogonal Decomposition: Rayleigh–Bénard Convection S Akbari, S Pawar, O San International Journal of Computational Fluid Dynamics 36 (7), 599-617, 2022 | 5 | 2022 |
Blending machine learning and sequential data assimilation over latent spaces for surrogate modeling of Boussinesq systems S Akbari, PH Dabaghian, O San Physica D: Nonlinear Phenomena 448, 133711, 2023 | 1 | 2023 |
A hybrid physics-based and data-driven approach with autoencoders: Rayleigh-Benard convection S Akbari, S Pawar, O San APS Division of Fluid Dynamics Meeting Abstracts, E31. 003, 2021 | 1 | 2021 |
Capacity Fade Analysis of Lithium-Ion Cells Utilizing Uncertainty Quantification Approach V Esfahanian, S Akbari, F Chaychizadeh, H Dehghandorost ECSarXiv, 2019 | 1 | 2019 |
Low-Rank Approximation with Time-Dependent Bases for Uncertainty Quantification Turbulent Reactive Flows S Akbari, MH Naderi, H Babaee Bulletin of the American Physical Society, 2023 | | 2023 |
A combined machine learning and data assimilation framework to model geophysical flows S Akbari, S Pawar, O San Bulletin of the American Physical Society 67, 2022 | | 2022 |