455 citations · 2.1k across the 56 of their papers we have counts for
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A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings
Mohammad Amin Khodkar, Pedram Hassanzadeh, Athanasios Antoulas
We introduce a data-driven method and shows its skills for spatiotemporal prediction of high-dimensional chaotic dynamics and turbulence. The method is based on a finite-dimensiona…
Analog forecasting of extreme-causing weather patterns using deep learning
Ashesh Chattopadhyay, Ebrahim Nabizadeh, Pedram Hassanzadeh
Numerical weather prediction (NWP) models require ever-growing computing time/resources, but still, have difficulties with predicting weather extremes. Here we introduce a data-dri…
Data-driven prediction of a multi-scale Lorenz 96 chaotic system using deep learning methods: Reservoir computing, ANN, and RNN-LSTM
Ashesh Chattopadhyay, Pedram Hassanzadeh, Devika Subramanian
In this paper, the performance of three deep learning methods for predicting short-term evolution and for reproducing the long-term statistics of a multi-scale spatio-temporal Lore…