Daniel Ries

Sandia National Laboratories — United States

Computer Science · Physical Sciences

5h-index88citations60works1.62yr avg
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Research Topics

Neural Networks and Applications(11), Neural Networks and Reservoir Computing(11), Physical Activity and Health(8), Fault Detection and Control Systems(7), Obesity, Physical Activity, Diet(5)

Publications60 total

Regression Recalibration by Learning PIT Map Values
Technometrics·2025· 1 citedOpen Access
Using feature importance as an exploratory data analysis tool on Earth system models
Geoscientific model development·2025· 1 citedOpen Access
Elastic Bayesian Model Calibration
SIAM/ASA Journal on Uncertainty Quantification·2025Open Access
An Explainable Pipeline for Machine Learning with Functional Data
arXiv (Cornell University)·2025Open Access
Multimodal data fusion for the joint estimation of plutonium oxide synthesis conditions
SSRN Electronic Journal·2025Open Access
Reply on RC1
2024Open Access
Reply on RC2
2024Open Access
Using feature importance as exploratory data analysis tool on earth system models
2024· 3 citedOpen Access
CLimate Impact: Determining Etiology thRough pAthways (CLDERA)
2024· 1 citedOpen Access
Explaining climatic pathways from stratospheric aerosol injections using feature importance on echo state networks
2024Open Access
Characterizing climate pathways using feature importance on echo state networks
Statistical Analysis and Data Mining The ASA Data Science Journal·2024· 5 citedOpen Access
Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data
Frontiers in Nuclear Engineering·2024· 2 citedOpen Access
Measuring the robustness of predictive probability for early stopping in two-group comparisons
Journal of Quality Technology·2024Open Access
Exploring regional pathways using feature importance with echo state networks
2024Open Access
A comparison of model validation approaches for echo state networks using climate model replicates
Spatial Statistics·2024· 12 citedOpen Access
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OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)·2024Open Access
Evaluating the quality of uncertainty quantification enabled deep learning models.
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)·2023Open Access
Characterizing climate pathways using feature importance on echo state networks
arXiv (Cornell University)·2023· 1 citedOpen Access
Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique
International Journal of Behavioral Nutrition and Physical Activity·2023· 2 citedOpen Access
Improving and Assessing the Quality of Uncertainty Quantification in Deep Learning
2023Open Access
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Frequent Co-authors

Katherine Goode(24), Kellie McClernon(13), James D. Tucker(13), Kurtis Shuler(8), Joshua Zollweg(7), Adah Zhang(6), Gabriel Huerta(6), Lyndsay Shand(6), Audrey McCombs(5), Madeline Ausdemore(4), Jason Adams(4), Robin P. Shook(3), Jason Y. Adams(3), Joshua Michalenko(3), Hung‐Wen Yeh(2), Gregory J. Welk(2), Benjamin Hillman(2), Lucas E. Sweet(2), Tyler Ganter(2), Alicia L. Carriquiry(2)