Member Since 1992
Juan M. Restrepo
Section Head, Mathematics In Computing, Oak Ridge National Laboratory
AGU Research
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Enhanced Short-term Weather Forecasts through Temporal Variation Encoding in Machine Learning Models
AGU 2024
atmospheric sciences | 12 december 2024
Ming Fan, Hyungyu Kang, Wei Zhang, Juan M. Restrep...
Machine learning (ML) techniques have emerged as a promising approach to improve regional weather forecast accuracy and reliability through data-drive...
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Understanding the Influences of Platform Motions on Floating Offshore Wind Turbine Power Generation and Wake Characteristics
AGU 2024
atmospheric sciences | 12 december 2024
Matthew R. Norman, Juan M. Restrepo, Stuart Slatte...
Floating offshore wind farms promise significant access to wind energy due to low surface friction and minimal surface obstacles. Reducing uncertainti...
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Tackling Epistemic and Aleatoric Forecast Errors in Wave Phenomena using Observations, Models, and Diffusion Map Machine Learning
EFFICIENT DATA-DRIVEN METHODS FOR MULTISCALE STOCHASTIC MODELING AND UNCERTAINTY QUANTIFICATION I ORAL
nonlinear geophysics | 13 december 2023
Juan M. Restrepo, Jorge M. Ramirez
Time dependent data assimilation is a well established Bayesian estimation strategy that take into account aleatoric errors in observations and models...
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Homotopy Sampling, with an Application to Particle Filters
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION II ORAL
nonlinear geophysics | 14 december 2021
Juan M. Restrepo, Jorge M. Ramirez
We describe a homotopy sampling procedure, loosely based on importance sampling. Starting from a known probability distribution, the homotopy procedur...
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Dynamic Likelihood Filter: A Data Assimilation Scheme that Exploits Hyperbolicity in Wave Problems to Propagate Observations
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION I
nonlinear geophysics | 14 december 2020
Dallas Foster, Juan M. Restrepo
We significantly extend the capabilities of the Dynamic Likelihood Filter, a data assimilation scheme tailor made for linear and nonlinear wave proble...
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Homotopy Data Assimilation
ADVANCES IN DATA ASSIMILATION, PREDICTABILITY, AND UNCERTAINTY QUANTIFICATION III POSTERS
nonlinear geophysics | 10 december 2019
Juan M. Restrepo, Robert Miller
We propose an importance sampling strategy that estimates the normalization for a target probability distribution, starting from a known distribution....
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Global Climate Change Forecasting Under Uncertainties
CENTENNIAL SESSION: COMPLEXITY OF NONLINEAR GEOPHYSICS: PAST ACCOMPLISHMENTS AND FUTURE CHALLENGES WITH AN EMPHASIS ON URBAN GEOSCIENCES I
nonlinear geophysics | 09 december 2019
Juan M. Restrepo, Michael E. Mann
'Climate is always changing' and 'it is not possible to make global climate forecasts due to uncertainties' are two widely held societal opinions that...
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