| Stable a posteriori LES of 2D turbulence using convolutional neural networks: Backscattering analysis and generalization to higher Re via transfer learning Y Guan, A Chattopadhyay, A Subel, P Hassanzadeh Journal of Computational Physics 458, 111090, 2022 | 73 | 2022 |
| Data-driven subgrid-scale modeling of forced Burgers turbulence using deep learning with generalization to higher Reynolds numbers via transfer learning A Subel, A Chattopadhyay, Y Guan, P Hassanzadeh Physics of Fluids 33 (3), 2021 | 70 | 2021 |
| Data‐driven super‐parameterization using deep learning: Experimentation with multiscale Lorenz 96 systems and transfer learning A Chattopadhyay, A Subel, P Hassanzadeh Journal of Advances in Modeling Earth Systems 12 (11), e2020MS002084, 2020 | 62 | 2020 |
| Learning physics-constrained subgrid-scale closures in the small-data regime for stable and accurate LES Y Guan, A Subel, A Chattopadhyay, P Hassanzadeh Physica D: Nonlinear Phenomena 443, 133568, 2023 | 34 | 2023 |
| Explaining the physics of transfer learning in data-driven turbulence modeling A Subel, Y Guan, A Chattopadhyay, P Hassanzadeh PNAS nexus 2 (3), pgad015, 2023 | 32 | 2023 |
| Building Ocean Climate Emulators A Subel, L Zanna arXiv preprint arXiv:2402.04342, 2024 | 1 | 2024 |
| Data-driven surrogate models for climate modeling: application of echo state networks, RNN-LSTM and ANN to the multi-scale Lorenz system as a test case A Chattopadhyay, K Ashesh, P Hassanzadeh, D Subramanian, K Palem, ... ICML 2019 Workshop on Climate Change: How Can AI Help?, 2019 | 1 | 2019 |
| Towards stable time-dependent climate emulation through the formulation of a boundary value problem A Subel, L Zanna AGU23, 2023 | | 2023 |
| Explainable deep learning for fluid dynamics using a Fourier-wavelet analysis framework P Hassanzadeh, A Chattopadhyay, Y Guan, H Pahlavan, A Subel Bulletin of the American Physical Society, 2023 | | 2023 |
| Integrating the spectral analyses of neural networks and climate physics for stable, explainable, and generalizable models P Hassanzadeh, Y Guan, A Subel, A Chattopadhyay APS March Meeting Abstracts 2023, W53. 006, 2023 | | 2023 |
| Explainable transfer learning for generalizable subgrid-scale modeling P Hassanzadeh, A Subel, AK Chattopadhyay, Y Guan, L Zanna, A Ross AGU Fall Meeting Abstracts 2022, NG16A-06, 2022 | | 2022 |
| Combining spectral analyses of turbulent flows and neural networks for explainable data-driven closure modeling P Hassanzadeh, A Subel, Y GUAN, A Chattopadhyay Bulletin of the American Physical Society 67, 2022 | | 2022 |
| Physics-Constrained Data-Driven Subgrid-Scale Models for Large Eddy Simulation in the Small-Data Regime Y Guan, A Subel, AK Chattopadhyay, P Hassanzadeh 102nd American Meteorological Society Annual Meeting, 2022 | | 2022 |
| Interpretable transfer learning: Applications to climate change modeling P Hassanzadeh, A Subel, A Chattopadhyay, Y Guan APS March Meeting Abstracts 2022, A10. 005, 2022 | | 2022 |
| Physics-constrained data-driven subgrid-scale parameterization of 2D turbulence in the small-data regime Y Guan, A Subel, A Chattopadhyay, P Hassanzadeh APS March Meeting Abstracts 2022, Q11. 010, 2022 | | 2022 |
| Data-driven subgrid-scale parameterization of forced 2D turbulence in the small-data limit Y Guan, A Subel, A Chattopadhyay, P Hassanzadeh AGU Fall Meeting Abstracts 2021, NG15A-0417, 2021 | | 2021 |
| Stable and accurate a posteriori LES of 2D turbulence with convolutional neural networks: Backscatter analysis and generalization via transfer learning Y Guan, A Chattopadhyay, A Subel, P Hassanzadeh EGU General Assembly Conference Abstracts, EGU21-402, 2021 | | 2021 |
| Data-driven subgrid-scale parameterization of turbulence in the small-data limit Y Guan, A Subel, A Chattopadhyay, P Hassanzadeh APS Division of Fluid Dynamics Meeting Abstracts, A11. 005, 2021 | | 2021 |
| Data-driven Super-prameterization in Climate Modeling with Recurrent Neural Networks and Transfer-Learning AK Chattopadhyay, A Subel, P Hassanzadeh AGU Fall Meeting Abstracts 2020, A068-0007, 2020 | | 2020 |
| Data-Driven Superparameterization Using Deep Learning: Experimentations with a Multiscale Lorenz 96 Model P Hassanzadeh, A Chattopadhyay, A Subel, K Palem 100th American Meteorological Society Annual Meeting, 2020 | | 2020 |
Ashesh ChattopadhyayUniversity of California, Santa CruzVerified email at ucsc.edu
