| Spontaneous aggregation of convective storms C Muller, D Yang, G Craig, T Cronin, B Fildier, JO Haerter, C Hohenegger, ... Annual Review of Fluid Mechanics 54 (1), 133-157, 2022 | 62 | 2022 |
| Implicit learning of convective organization explains precipitation stochasticity S Shamekh, KD Lamb, Y Huang, P Gentine PNAS, 2022 | 49 | 2022 |
| How do ocean warm anomalies favor the aggregation of deep convective clouds? S Shamekh, C Muller, JP Duvel, F d’Andrea Journal of the Atmospheric Sciences 77 (11), 3733-3745, 2020 | 29 | 2020 |
| ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation S Yu, W Hannah, L Peng, J Lin, MA Bhouri, R Gupta, B Lütjens, JC Will, ... Advances in Neural Information Processing Systems 36, 22070-22084, 2023 | 25 | 2023 |
| Self‐aggregation of convective clouds with interactive sea surface temperature S Shamekh, C Muller, JP Duvel, F d'Andrea Journal of Advances in Modeling Earth Systems 12 (11), e2020MS002164, 2020 | 24 | 2020 |
| ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators S Yu, WM Hannah, L Peng, MA Bhouri, R Gupta, J Lin, B Lütjens, JC Will, ... NeurIPS, 2023 | 13 | 2023 |
| Significant amplification of instantaneous extreme precipitation with convective self‐aggregation NA Da Silva, C Muller, S Shamekh, B Fildier Journal of Advances in Modeling Earth Systems 13 (11), e2021MS002607, 2021 | 8 | 2021 |
| Learning atmospheric boundary layer turbulence S Shamekh, P Gentine Authorea Preprints, 2023 | 3 | 2023 |
| Systematically generating hierarchies of machine-learning models, from equation discovery to deep neural networks (core science keynote) TG Beucler, A Grundner, R Lagerquist, S Shamekh 103rd AMS Annual Meeting, 2023 | 1 | 2023 |
| Learning Machine Learning with Lorenz-96 D Balwada, R Abernathey, S Acharya, A Adcroft, J Brener, V Balaji, ... Journal of Open Source Education 7 (82), 241, 2024 | | 2024 |
| Developing an Interpretable Model for Convective Precipitation Using Machine Learning S Shamekh, P Angulo-Umana AGU24, 2024 | | 2024 |
| Data-Driven Science: Developments in Machine Learning Subgrid-Scale Parameterizations and in Reanalyses Across Earth System Modeling II Poster S Driscoll, S Shamekh, A Kumar, A Sane, L Mansfield, MG Bosilovich, ... AGU24, 2024 | | 2024 |
| Interpretable Machine Learning-based Radiation Emulation for ICON K Hafner, F Iglesias-Suarez, S Shamekh, P Gentine, MA Giorgetta, ... Authorea Preprints, 2024 | | 2024 |
| Distilling Machine Learning's Added Value: Pareto Fronts in Atmospheric Applications T Beucler, A Grundner, S Shamekh, P Ukkonen, M Chantry, R Lagerquist arXiv preprint arXiv:2408.02161, 2024 | | 2024 |
| ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation S Akshay, S Yu, W Hannah, L Peng, J Lin, MA Bhouri, G Ritwik, B Lütjens, ... | | 2024 |
| Learning Machine Learning with Lorenz-96 D Balwada, R Abernathey, S Acharya, A Adcroft, J Brener, V Balaji, ... Authorea Preprints, 2023 | | 2023 |
| Large and Increasing Soil Moisture Impact on West European Heatwaves Y Huang, X Lian, J Liu, O Skulovich, S Shamekh, P Gentine AGU Fall Meeting Abstracts 2023, GC33A-04, 2023 | | 2023 |
| Improvement of the radiation parameterization of ICON by including subgrid-scale cloud properties using machine learning K Hafner, F Iglesias-Suarez, S Shamekh, P Gentine, R Pincus, GA Marco, ... AGU Fall Meeting Abstracts 2023, NG31A-02, 2023 | | 2023 |
| Physics to machine learning, and machine learning back to physics P Gentine, S Shamekh, A Anderson-Connolly, T Beucler, V Eyring, ... AGU Fall Meeting Abstracts 2022, NG15A-05, 2022 | | 2022 |
| Low-dimensional representation of turbulence across planetary boundary layer regimes P Gentine, S Shamekh AGU Fall Meeting Abstracts 2022, A43C-03, 2022 | | 2022 |