Sara Shamekh

According to our database, Sara Shamekh authored at least 14 papers between 2023 and 2026.

Collaborative distances:

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

2026

Wavelet Flow Matching for Multi-Scale Physics Emulation.

Gabriele Accarino, Juan Nathaniel, Carla Roesch, Pierre Gentine, Sara Shamekh, Duncan Watson-Parris, Viviana Acquaviva

CoRR, May, 2026

Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning.

Savannah L. Ferretti, Jerry Lin, Sara Shamekh, Jane W. Baldwin, Michael S. Pritchard, Tom Beucler

CoRR, March, 2026

2025

WaveSim: A Wavelet-based Multi-scale Similarity Metric for Weather and Climate Fields.

Gabriele Accarino, Viviana Acquaviva, Sara Shamekh, Duncan Watson-Parris, David Lawrence

CoRR, December, 2025

CuMoLoS-MAE: A Masked Autoencoder for Remote Sensing Data Reconstruction.

Anurup Naskar, Nathanael Zhixin Wong, Sara Shamekh

CoRR, August, 2025

PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models.

Yongquan Qu, Matthieu Blanke, Sara Shamekh, Pierre Gentine

CoRR, August, 2025

Strictly Constrained Generative Modeling via Split Augmented Langevin Sampling.

Matthieu Blanke, Yongquan Qu, Sara Shamekh, Pierre Gentine

CoRR, May, 2025

ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation.

Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Helge Heuer, Benjamin R. Hillman, Andrea M. Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth A. Barnes, Noah D. Brenowitz, Christopher S. Bretherton, Veronika Eyring, Savannah L. Ferretti, Nicholas J. Lutsko, Pierre Gentine, Stephan Mandt, J. David Neelin, Rose Yu, Laure Zanna, Nathan M. Urban, Janni Yuval, Ryan Abernathey, Pierre Baldi, Wayne Chuang, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Po-Lun Ma, Sara Shamekh, Guang Zhang, Michael S. Pritchard

J. Mach. Learn. Res., 2025

2024

Learning Machine Learning with Lorenz-96.

Dhruv Balwada, Ryan Abernathey, Shantanu Acharya, Alistair Adcroft, Judith Berner, Venkatramani Balaji, Mohamed Aziz Bhouri, Joan Bruna, Mitch Bushuk, William E. Chapman, Alex Connolly, Julie Deshayes, Carlos Fernandez-Granda, Pierre Gentine, Anastasiia Gorbunova, Will Gregory, Arthur P. Guillaumin, Shubham Gupta, Marika M. Holland, J. Emmanuel Johnsson, Julien Le Sommer, Ziwei Li, Nora Loose, Feiyu Lu, Paul O'Gorman, Pavel Perezhogin, Brandon Reichl, Andrew Slavin Ross, Aakash Sane, Sara Shamekh, Tarun Verma, Janni Yuval, Lorenzo Zampieri, Cheng Zhang, Laure Zanna

Dataset, December, 2024

m2lines/L96_demo: Final version for JOSE with DOIs.

Dhruv Balwada, Ryan Abernathey, Shantanu Acharya, Alistair Adcroft, Judith Berner, Venkatramani Balaji, Mohamed Aziz Bhouri, Joan Bruna, Mitch Bushuk, William E. Chapman, Alex Connolly, Julie Deshayes, Carlos Fernandez-Granda, Pierre Gentine, Anastasiia Gorbunova, Will Gregory, Arthur Guillaumin, Shubham Gupta, Johanna Goldman, Marika M. Holland, J. Emmanuel Johnsson, Julien Le Sommer, Ziwei Li, Nora Loose, Feiyu Lu, Paul O'Gorman, Pavel Perezhogin, Brandon Reichl, Andrew Slavin Ross, Aakash Sane, Sara Shamekh, Tarun Verma, Janni Yuval, Lorenzo Zampieri, Cheng Zhang, Laure Zanna

Dataset, August, 2024

m2lines/L96_demo: Final version for JOSE.

Dhruv Balwada, Ryan Abernathey, Shantanu Acharya, Alistair Adcroft, Judith Brenner, Venkatramani Balaji, Mohamed Aziz Bhouri, Joan Bruna, Mitch Bushuk, William E. Chapman, Alex Connolly, Julie Deshayes, Carlos Fernandez-Granda, Pierre Gentine, Anastasiia Gorbunova, Will Gregory, Arthur Guillaumin, Shubham Gupta, Marika M. Holland, J. Emmanuel Johnsson, Julien Le Sommer, Zhiwei Li, Nora Loose, Feiyu Lu, Paul O'Gorman, Pavel Perezhogin, Brandon Reichl, Andrew Slavin Ross, Aakash Sane, Sara Shamekh, Tarun Verma, Janni Yuval, Lorenzo Zampieri, Cheng Zhang, Laure Zanna

Dataset, August, 2024

m2lines/L96_demo: v1.0.1.

Dhruv Balwada, Ryan Abernathey, Shantanu Acharya, Alistair Adcroft, Judith Berner, Venkatramani Balaji, Mohamed Aziz Bhouri, Joan Bruna, Mitch Bushuk, William E. Chapman, Alex Connolly, Julie Deshayes, Carlos Fernandez-Granda, Pierre Gentine, Anastasiia Gorbunova, Will Gregory, Shubham Gupta, Arthur Guillaumin, Marika M. Holland, J. Emmanuel Johnsson, Julien Le Sommer, Zhiwei Li, Nora Loose, Feiyu Lu, Paul O'Gorman, Pavel Perezhogin, Brandon Reichl, Andrew Slavin Ross, Aakash Sane, Sara Shamekh, Tarun Verma, Janni Yuval, Lorenzo Zampieri, Cheng Zhang, Laure Zanna

Dataset, August, 2024

Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications.

Tom Beucler, Arthur Grundner, Sara Shamekh, Peter Ukkonen, Matthew Chantry, Ryan Lagerquist

CoRR, 2024

2023

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

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.

CoRR, 2023

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023