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05/15/2023
Black-Box Statistical Prediction of Lossy Compression Ratios for Scientific Data
Lossy compressors are increasingly adopted in scientific research, tackl...
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11/30/2022
Statistical treatment of convolutional neural network super-resolution of inland surface wind for subgrid-scale variability quantification
Machine learning models are frequently employed to perform either purely...
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11/24/2022
Joint modeling of wind speed and wind direction through a conditional approach
Atmospheric near surface wind speed and wind direction play an important...
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05/03/2022
Station-wise statistical joint assessment of wind speed and direction under future climates across the United States
This study develops a statistical conditional approach to evaluate clima...
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11/27/2021
Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets
Lossy compression plays a growing role in scientific simulations where t...
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10/19/2021
Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails
In traditional extreme value analysis, the bulk of the data is ignored, ...
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07/29/2021
Neural Networks for Parameter Estimation in Intractable Models
We propose to use deep learning to estimate parameters in statistical mo...
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01/08/2021
SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors
Efficient error-controlled lossy compressors are becoming critical to th...
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12/12/2020
Parameter Estimation with Dense and Convolutional Neural Networks Applied to the FitzHugh-Nagumo ODE
Machine learning algorithms have been successfully used to approximate n...
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10/15/2018
Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms
This paper introduces a statistical treatment of inverse problems constr...
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06/10/2018
Forecast evaluation with imperfect observations and imperfect models
The field of statistics has become one of the mathematical foundations i...
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08/24/2017