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2020 – today
- 2024
[i20]Peter Manshausen, Yair Cohen, Jaideep Pathak, Mike Pritchard, Piyush Garg, Morteza Mardani, Karthik Kashinath, Simon Byrne, Noah D. Brenowitz:
Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales. CoRR abs/2406.16947 (2024)- [i19]Ankur Mahesh, William D. Collins, Boris Bonev, Noah D. Brenowitz, Yair Cohen, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis A. O'Brien, Michael S. Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard:
Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators. CoRR abs/2408.01581 (2024) - [i18]Ankur Mahesh, William D. Collins, Boris Bonev, Noah D. Brenowitz, Yair Cohen, Joshua Elms, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis A. O'Brien, Michael S. Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, Jared Willard:
Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators. CoRR abs/2408.03100 (2024) - [i17]Jaideep Pathak, Yair Cohen, Piyush Garg, Peter Harrington, Noah D. Brenowitz, Dale R. Durran, Morteza Mardani, Arash Vahdat, Shaoming Xu, Karthik Kashinath, Michael S. Pritchard:
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling. CoRR abs/2408.10958 (2024) - 2023
- [j3]Torsten Hoefler
, Bjorn Stevens, Andreas F. Prein, Johanna Baehr, Thomas C. Schulthess, Thomas F. Stocker, John A. Taylor, Daniel Klocke, Pekka Manninen, Piers M. Forster, Tobias Kölling, Nicolas Gruber, Hartwig Anzt, Claudia Frauen, Florian Ziemen, Milan Klöwer, Karthik Kashinath, Christoph M. Schär, Oliver Fuhrer, Bryan N. Lawrence:
Earth Virtualization Engines: A Technical Perspective. Comput. Sci. Eng. 25(3): 50-59 (2023) - [c10]Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar:
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. ICML 2023: 2806-2823 - [c9]Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard:
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS 2023 - [c8]Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Anima Anandkumar:
FourCastNet: Accelerating Global High-Resolution Weather Forecasting Using Adaptive Fourier Neural Operators. PASC 2023: 13:1-13:11 - [i16]Adam Rupe, Karthik Kashinath, Nalini Kumar, James P. Crutchfield:
Physics-Informed Representation Learning for Emergent Organization in Complex Dynamical Systems. CoRR abs/2304.12586 (2023) - [i15]Boris Bonev, Thorsten Kurth, Christian Hundt, Jaideep Pathak, Maximilian Baust, Karthik Kashinath, Anima Anandkumar:
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. CoRR abs/2306.03838 (2023) - [i14]Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.:
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR abs/2306.08754 (2023) - [i13]Torsten Hoefler, Bjorn Stevens, Andreas F. Prein, Johanna Baehr, Thomas C. Schulthess, Thomas F. Stocker, John A. Taylor, Daniel Klocke, Pekka Manninen, Piers M. Forster, Tobias Kölling, Nicolas Gruber, Hartwig Anzt, Claudia Frauen, Florian Ziemen, Milan Klöwer, Karthik Kashinath, Christoph M. Schär, Oliver Fuhrer, Bryan N. Lawrence:
Earth Virtualization Engines - A Technical Perspective. CoRR abs/2309.09002 (2023) - [i12]Morteza Mardani, Noah D. Brenowitz, Yair Cohen, Jaideep Pathak, Chieh-Yu Chen, Cheng-Chin Liu, Arash Vahdat, Karthik Kashinath, Jan Kautz, Mike Pritchard:
Generative Residual Diffusion Modeling for Km-scale Atmospheric Downscaling. CoRR abs/2309.15214 (2023) - [i11]Oliver Watt-Meyer, Gideon Dresdner, Jeremy McGibbon, Spencer K. Clark, Brian Henn, James Duncan, Noah D. Brenowitz, Karthik Kashinath, Michael S. Pritchard, Boris Bonev, Matthew E. Peters, Christopher S. Bretherton:
ACE: A fast, skillful learned global atmospheric model for climate prediction. CoRR abs/2310.02074 (2023) - 2022
- [i10]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) - [i9]Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Animashree Anandkumar:
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators. CoRR abs/2208.05419 (2022) - [i8]Tao Ge, Jaideep Pathak, Akshay Subramaniam, Karthik Kashinath:
DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting. CoRR abs/2210.12293 (2022) - 2021
- [i7]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) - 2020
- [j2]Jinlong Wu, Karthik Kashinath, Adrian Albert, Dragos Chirila, Prabhat, Heng Xiao:
Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems. J. Comput. Phys. 406: 109209 (2020) - [c7]Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Karthik Kashinath:
Deep spatial transformers for autoregressive data-driven forecasting of geophysical turbulence. CI 2020: 106-112 - [c6]Grzegorz Muszynski, Prabhat, Jan Balewski, Karthik Kashinath, Michael F. Wehner, Vitaliy Kurlin:
Atmospheric Blocking Pattern Recognition in Global Climate Model Simulation Data. ICPR 2020: 677-684 - [c5]Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu:
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. KDD 2020: 1457-1466 - [c4]Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar:
MeshfreeFlowNet: a physics-constrained deep continuous space-time super-resolution framework. SC 2020: 9 - [i6]Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar:
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework. CoRR abs/2005.01463 (2020) - [i5]Jaideep Pathak, Mustafa Mustafa, Karthik Kashinath, Emmanuel Motheau, Thorsten Kurth, Marcus Day:
Using Machine Learning to Augment Coarse-Grid Computational Fluid Dynamics Simulations. CoRR abs/2010.00072 (2020)
2010 – 2019
- 2019
- [c3]Chiyu Max Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Nießner:
Spherical CNNs on Unstructured Grids. ICLR (Poster) 2019 - [c2]Adam Rupe, Prabhat, James P. Crutchfield, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor W. Lee:
DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems. MLHPC@SC 2019: 75-87 - [c1]Sookyung Kim, Hyojin Kim, Joonseok Lee, Sangwoong Yoon, Samira Ebrahimi Kahou, Karthik Kashinath, Prabhat:
Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events. WACV 2019: 1761-1769 - [i4]Chiyu Max Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Nießner:
Spherical CNNs on Unstructured Grids. CoRR abs/1901.02039 (2019) - [i3]Adam Rupe, Karthik Kashinath, Nalini Kumar, Victor W. Lee, Prabhat, James P. Crutchfield:
Towards Unsupervised Segmentation of Extreme Weather Events. CoRR abs/1909.07520 (2019) - [i2]Adam Rupe, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor W. Lee, Prabhat, James P. Crutchfield:
DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems. CoRR abs/1909.11822 (2019) - [i1]Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu:
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. CoRR abs/1911.08655 (2019) - 2016
- [j1]Travis A. O'Brien, Karthik Kashinath, Nicholas R. Cavanaugh, William D. Collins, John P. O'Brien:
A fast and objective multidimensional kernel density estimation method: fastKDE. Comput. Stat. Data Anal. 101: 148-160 (2016)
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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