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ORCIDAshesh Chattopadhyay
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2020 – today
- 2024
[i15]Haiwen Guan, Troy Arcomano, Ashesh Chattopadhyay, Romit Maulik:
LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles. CoRR abs/2405.16297 (2024)- [i14]Dibyajyoti Chakraborty, Seung Whan Chung, Ashesh Chattopadhyay, Romit Maulik:
Improved deep learning of chaotic dynamical systems with multistep penalty losses. CoRR abs/2410.05572 (2024) - [i13]Y. Qiang Sun, Pedram Hassanzadeh, Mohsen Zand, Ashesh Chattopadhyay, Jonathan Weare, Dorian S. Abbot:
Can AI weather models predict out-of-distribution gray swan tropical cyclones? CoRR abs/2410.14932 (2024) - 2023
- [j2]Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach
, Pedram Hassanzadeh:
Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems. J. Comput. Phys. 477: 111918 (2023) - [i12]Ashesh Chattopadhyay, Pedram Hassanzadeh:
Long-term instabilities of deep learning-based digital twins of the climate system: The cause and a solution. CoRR abs/2304.07029 (2023) - [i11]Karan Jakhar, Yifei Guan, Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh, Laura Zanna:
Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges. CoRR abs/2306.05014 (2023) - [i10]Ashesh Chattopadhyay, Michael Gray, Tianning Wu, Anna B. Lowe, Ruoying He:
OceanNet: A principled neural operator-based digital twin for regional oceans. CoRR abs/2310.00813 (2023) - 2022
- [j1]Yifei Guan, Ashesh Chattopadhyay, Adam Subel, Pedram Hassanzadeh:
Stable a posteriori LES of 2D turbulence using convolutional neural networks: Backscattering analysis and generalization to higher Re via transfer learning. J. Comput. Phys. 458: 111090 (2022) - [i9]Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, Pedram Hassanzadeh, Karthik Kashinath, Animashree Anandkumar:
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR abs/2202.11214 (2022) - [i8]Ashesh Chattopadhyay, Jaideep Pathak, Ebrahim Nabizadeh, Wahid Bhimji, Pedram Hassanzadeh:
Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence. CoRR abs/2205.04601 (2022) - [i7]Adam Subel, Yifei Guan, Ashesh Chattopadhyay, Pedram Hassanzadeh:
Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow. CoRR abs/2206.03198 (2022) - [i6]Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach, Pedram Hassanzadeh:
Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems. CoRR abs/2206.04811 (2022) - 2021
- [i5]Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Eviatar Bach, Karthik Kashinath:
Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers. CoRR abs/2103.09360 (2021) - [i4]Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh:
Closed-form discovery of structural errors in models of chaotic systems by integrating Bayesian sparse regression and data assimilation. CoRR abs/2110.00546 (2021) - 2020
- [c2]Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Karthik Kashinath:
Deep spatial transformers for autoregressive data-driven forecasting of geophysical turbulence. CI 2020: 106-112
2010 – 2019
- 2019
- [i3]Ashesh Chattopadhyay, Pedram Hassanzadeh, Krishna V. Palem, Devika Subramanian:
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using a hierarchy of deep learning methods: Reservoir computing, ANN, and RNN-LSTM. CoRR abs/1906.08829 (2019) - [i2]Ashesh Chattopadhyay, Ebrahim Nabizadeh, Pedram Hassanzadeh:
Analog forecasting of extreme-causing weather patterns using deep learning. CoRR abs/1907.11617 (2019) - 2018
- [i1]Ashesh Chattopadhyay, Pedram Hassanzadeh, Saba Pasha:
A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns. CoRR abs/1811.04817 (2018) - 2016
- [c1]V. M. Krushnarao Kotteda, Ashesh Chattopadhyay, Vinod Kumar, William F. Spotz:
A framework to integrate MFiX with Trilinos for high fidelity fluidized bed computations. HPEC 2016: 1-6
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