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

Mar 16, 2021
Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Eviatar Bach, Karthik Kashinath

* Under review in Geoscientific Model Development 

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Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations

Oct 03, 2020
Jaideep Pathak, Mustafa Mustafa, Karthik Kashinath, Emmanuel Motheau, Thorsten Kurth, Marcus Day

* Corrected typographical errors in the previous version related to the incorrectly formatted accented character "\'e" appearing in various places in the manuscript 

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MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

May 01, 2020
Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar

* Supplementary Video: 

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Towards Physics-informed Deep Learning for Turbulent Flow Prediction

Dec 21, 2019
Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu

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DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems

Sep 25, 2019
Adam Rupe, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor Lee, Prabhat, James P. Crutchfield

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Towards Unsupervised Segmentation of Extreme Weather Events

Sep 16, 2019
Adam Rupe, Karthik Kashinath, Nalini Kumar, Victor Lee, Prabhat, James P. Crutchfield

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Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems

May 13, 2019
Jin-Long Wu, Karthik Kashinath, Adrian Albert, Dragos Chirila, Prabhat, Heng Xiao

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Spherical CNNs on Unstructured Grids

Jan 07, 2019
Chiyu "Max" Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Niessner

* Accepted as a conference paper at ICLR 2019. Codes available at 

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