Pedram Hassanzadeh

27 papers Journal 26Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Decision-oriented benchmarking to transform AI weather forecast access: Application to the Indian monsoon. CoRR Rajat Masiwal, Colin Aitken, Adam Marchakitus, Mayank Gupta, Katherine Kowal, Hamid A. Pahlavan, Tyler Yang, Y. Qiang Sun, Michael Kremer, Amir Jina, William R. Boos, Pedram Hassanzadeh
2026	J	`jnl`	Designing probabilistic AI monsoon forecasts to inform agricultural decision-making. CoRR Colin Aitken, Rajat Masiwal, Adam Marchakitus, Katherine Kowal, Mayank Gupta, Tyler Yang, Amir Jina, Pedram Hassanzadeh, William R. Boos, Michael Kremer
2025	J	`jnl`	An Analytical and AI-discovered Stable, Accurate, and Generalizable Subgrid-scale Closure for Geophysical Turbulence. CoRR Karan Jakhar, Yifei Guan, Pedram Hassanzadeh
2025	J	`jnl`	Benchmarking atmospheric circulation variability in an AI emulator, ACE2, and a hybrid model, NeuralGCM. CoRR Ian Baxter, Hamid A. Pahlavan, Pedram Hassanzadeh, Katharine Rucker, Tiffany Shaw
2025	J	`jnl`	Deep learning the sources of MJO predictability: a spectral view of learned features. CoRR Lin Yao, Da Yang, James P. C. Duncan, Ashesh Chattopadhyay, Pedram Hassanzadeh, Wahid Bhimji, Bin Yu
2025	J	`jnl`	Fourier analysis of the physics of transfer learning for data-driven subgrid-scale models of ocean turbulence. CoRR Moein Darman, Pedram Hassanzadeh, Laure Zanna, Ashesh Chattopadhyay
2025	J	`jnl`	Hierarchical Implicit Neural Emulators. CoRR Ruoxi Jiang, Xiao Zhang, Karan Jakhar, Peter Y. Lu, Pedram Hassanzadeh, Michael Maire, Rebecca Willett
2025	J	`jnl`	Reframing Generative Models for Physical Systems using Stochastic Interpolants. CoRR Anthony Y. Zhou, Alexander Wikner, Amaury Lancelin, Pedram Hassanzadeh, Amir Barati Farimani
2024	J	`jnl`	Can AI weather models predict out-of-distribution gray swan tropical cyclones? CoRR Y. Qiang Sun, Pedram Hassanzadeh, Mohsen Zand, Ashesh Chattopadhyay, Jonathan Weare, Dorian S. Abbot
2024	J	`jnl`	On the importance of learning non-local dynamics for stable data-driven climate modeling: A 1D gravity wave-QBO testbed. CoRR Hamid A. Pahlavan, Pedram Hassanzadeh, M. Joan Alexander
2023	J	`jnl`	Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems. J. Comput. Phys. Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach, Pedram Hassanzadeh
2023	J	`jnl`	Extreme Event Prediction with Multi-agent Reinforcement Learning-based Parametrization of Atmospheric and Oceanic Turbulence. CoRR Rambod Mojgani, Daniel Wälchli, Yifei Guan, Petros Koumoutsakos, Pedram Hassanzadeh
2023	J	`jnl`	Learning Closed-form Equations for Subgrid-scale Closures from High-fidelity Data: Promises and Challenges. CoRR Karan Jakhar, Yifei Guan, Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh, Laura Zanna
2023	J	`jnl`	Long-term instabilities of deep learning-based digital twins of the climate system: The cause and a solution. CoRR Ashesh Chattopadhyay, Pedram Hassanzadeh
2022	J	`jnl`	Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems. CoRR Ashesh Chattopadhyay, Ebrahim Nabizadeh, Eviatar Bach, Pedram Hassanzadeh
2022	J	`jnl`	Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow. CoRR Adam Subel, Yifei Guan, Ashesh Chattopadhyay, Pedram Hassanzadeh
2022	J	`jnl`	FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR 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
2022	J	`jnl`	Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks. CoRR Rambod Mojgani, Maciej Balajewicz, Pedram Hassanzadeh
2022	J	`jnl`	Long-term stability and generalization of observationally-constrained stochastic data-driven models for geophysical turbulence. CoRR Ashesh Chattopadhyay, Jaideep Pathak, Ebrahim Nabizadeh, Wahid Bhimji, Pedram Hassanzadeh
2022	J	`jnl`	Stable J. Comput. Phys. Yifei Guan, Ashesh Chattopadhyay, Adam Subel, Pedram Hassanzadeh
2021	J	`jnl`	A data-driven, physics-informed framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings. J. Comput. Phys. M. A. Khodkar, Pedram Hassanzadeh
2021	J	`jnl`	Closed-form discovery of structural errors in models of chaotic systems by integrating Bayesian sparse regression and data assimilation. CoRR Rambod Mojgani, Ashesh Chattopadhyay, Pedram Hassanzadeh
2021	J	`jnl`	Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers. CoRR Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Eviatar Bach, Karthik Kashinath
2020	—	`conf`	Deep spatial transformers for autoregressive data-driven forecasting of geophysical turbulence. CI Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Karthik Kashinath
2019	J	`jnl`	Analog forecasting of extreme-causing weather patterns using deep learning. CoRR Ashesh Chattopadhyay, Ebrahim Nabizadeh, Pedram Hassanzadeh
2019	J	`jnl`	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 Ashesh Chattopadhyay, Pedram Hassanzadeh, Krishna V. Palem, Devika Subramanian
2018	J	`jnl`	A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns. CoRR Ashesh Chattopadhyay, Pedram Hassanzadeh, Saba Pasha