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ORCIDIan G. Grooms
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2020 – today
- 2024
[j13]Ian G. Grooms
, Christopher Riedel:
A Quantile-Conserving Ensemble Filter Based on Kernel-Density Estimation. Remote. Sens. 16(13): 2377 (2024)- 2022
- [j12]Nora Loose, Ryan Abernathey, Ian G. Grooms, Julius Busecke, Arthur Guillaumin, Elizabeth Yankovsky, Gustavo Marques, Jacob Steinberg, Andrew Slavin Ross, Hemant Khatri, Scott Bachman, Laure Zanna, Paige Martin:
GCM-Filters: A Python Package for Diffusion-based Spatial Filtering of Gridded Data. J. Open Source Softw. 7(69): 3947 (2022) - 2021
- [j11]Lucia Minah Yang, Ian G. Grooms, Keith A. Julien:
The fidelity of exponential and IMEX integrators for wave turbulence: Introduction of a new near-minimax integrating factor scheme. J. Comput. Phys. 434: 109992 (2021) - [j10]Lucia Minah Yang, Ian G. Grooms, Keith A. Julien:
Corrigendum to "The fidelity of exponential and IMEX integrators for wave turbulence: Introduction of a new near-minimax integrating factor scheme" [J. Comput. Phys. 434 (2021) 109992]. J. Comput. Phys. 439: 110372 (2021) - [j9]Lucia Minah Yang, Ian G. Grooms:
Machine learning techniques to construct patched analog ensembles for data assimilation. J. Comput. Phys. 443: 110532 (2021) - [i3]Lucia Minah Yang, Ian G. Grooms:
Machine Learning Techniques to Construct Patched Analog Ensembles for Data Assimilation. CoRR abs/2103.00318 (2021) - 2020
- [j8]Gregor A. Robinson, Ian G. Grooms:
A Fast Tunable Blurring Algorithm for Scattered Data. SIAM J. Sci. Comput. 42(4): A2281-A2299 (2020) - [i2]Ian G. Grooms:
Analog ensemble data assimilation and a method for constructing analogs with variational autoencoders. CoRR abs/2006.01101 (2020)
2010 – 2019
- 2019
- [j7]Matthew Watwood, Ian G. Grooms, Keith A. Julien, K. Shafer Smith:
Energy-conserving Galerkin approximations for quasigeostrophic dynamics. J. Comput. Phys. 388: 23-40 (2019) - [i1]Gregor A. Robinson, Ian G. Grooms:
A tunable multiresolution smoother for scattered data with application to particle filtering. CoRR abs/1906.06722 (2019) - 2015
- [j6]Ian G. Grooms, Yoonsang Lee, Andrew J. Majda:
Numerical Schemes for Stochastic Backscatter in the Inverse Cascade of Quasigeostrophic Turbulence. Multiscale Model. Simul. 13(3): 1001-1021 (2015) - 2014
- [j5]Andrew J. Majda, Ian G. Grooms:
New perspectives on superparameterization for geophysical turbulence. J. Comput. Phys. 271: 60-77 (2014) - [j4]Ian G. Grooms, Andrew J. Majda:
Stochastic superparameterization in quasigeostrophic turbulence. J. Comput. Phys. 271: 78-98 (2014) - [j3]Ian G. Grooms, Yoonsang Lee, Andrew J. Majda:
Ensemble Kalman filters for dynamical systems with unresolved turbulence. J. Comput. Phys. 273: 435-452 (2014) - 2011
- [j2]Ian G. Grooms, Keith A. Julien:
Linearly implicit methods for nonlinear PDEs with linear dispersion and dissipation. J. Comput. Phys. 230(9): 3630-3650 (2011)
2000 – 2009
- 2009
- [j1]Ian G. Grooms, Robert Michael Lewis, Michael W. Trosset:
Molecular Embedding via a Second Order Dissimilarity Parameterized Approach. SIAM J. Sci. Comput. 31(4): 2733-2756 (2009)
Coauthor Index
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