Ashesh Chattopadhyay

According to our database, Ashesh Chattopadhyay authored at least 17 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Improved deep learning of chaotic dynamical systems with multistep penalty losses.

Dibyajyoti Chakraborty, Seung Whan Chung, Ashesh Chattopadhyay, Romit Maulik

CoRR, 2024

LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles.

Haiwen Guan, Troy Arcomano, Ashesh Chattopadhyay, Romit Maulik

CoRR, 2024

2023

Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems.

Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach, Pedram Hassanzadeh

J. Comput. Phys., March, 2023

OceanNet: A principled neural operator-based digital twin for regional oceans.

Ashesh Chattopadhyay, Michael Gray, Tianning Wu, Anna B. Lowe, Ruoying He

CoRR, 2023

Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges.

Karan Jakhar, Yifei Guan, Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh, Laura Zanna

CoRR, 2023

Long-term instabilities of deep learning-based digital twins of the climate system: The cause and a solution.

Ashesh Chattopadhyay, Pedram Hassanzadeh

CoRR, 2023

2022

Stable <i>a posteriori</i> LES of 2D turbulence using convolutional neural networks: Backscattering analysis and generalization to higher <i>Re</i> via transfer learning.

Yifei Guan, Ashesh Chattopadhyay, Adam Subel, Pedram Hassanzadeh

J. Comput. Phys., 2022

Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow.

Adam Subel, Yifei Guan, Ashesh Chattopadhyay, Pedram Hassanzadeh

CoRR, 2022

Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence.

Ashesh Chattopadhyay, Jaideep Pathak, Ebrahim Nabizadeh, Wahid Bhimji, Pedram Hassanzadeh

CoRR, 2022

FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

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

CoRR, 2022

2021

Closed-form discovery of structural errors in models of chaotic systems by integrating Bayesian sparse regression and data assimilation.

Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh

CoRR, 2021

Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers.

Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Eviatar Bach, Karthik Kashinath

CoRR, 2021

2020

Deep spatial transformers for autoregressive data-driven forecasting of geophysical turbulence.

Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Karthik Kashinath

Proceedings of the CI 2020: 10th International Conference on Climate Informatics, 2020

2019

Analog forecasting of extreme-causing weather patterns using deep learning.

Ashesh Chattopadhyay, Ebrahim Nabizadeh, Pedram Hassanzadeh

CoRR, 2019

Data-driven prediction of a multi-scale Lorenz 96 chaotic system using a hierarchy of deep learning methods: Reservoir computing, ANN, and RNN-LSTM.

Ashesh Chattopadhyay, Pedram Hassanzadeh, Krishna V. Palem, Devika Subramanian

CoRR, 2019

2018

A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns.

Ashesh Chattopadhyay, Pedram Hassanzadeh, Saba Pasha

CoRR, 2018

2016

A framework to integrate MFiX with Trilinos for high fidelity fluidized bed computations.

V. M. Krushnarao Kotteda, Ashesh Chattopadhyay, Vinod Kumar, William F. Spotz

Proceedings of the 2016 IEEE High Performance Extreme Computing Conference, 2016