Daniel Ries

11 papers C 1Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An Explainable Pipeline for Machine Learning with Functional Data. CoRR Katherine Goode, J. Derek Tucker, Daniel Ries, Heike Hofmann
2025	J	`jnl`	Elastic Bayesian Model Calibration. SIAM/ASA J. Uncertain. Quantification Devin Francom, J. Derek Tucker, Gabriel Huerta, Kurtis Shuler, Daniel Ries
2025	J	`jnl`	Regression Recalibration by Learning PIT Map Values. Technometrics Christopher Qian, Daniel Ries, Feng Liang, Jason Adams
2024	J	`jnl`	Characterizing climate pathways using feature importance on echo state networks. Stat. Anal. Data Min. Katherine Goode, Daniel Ries, Kellie McClernon
2023	J	`jnl`	A Framework for Inverse Prediction Using Functional Response Data. J. Comput. Inf. Sci. Eng. Daniel Ries, Adah Zhang, J. Derek Tucker, Kurtis Shuler, Madeline Ausdemore
2023	J	`jnl`	Characterizing climate pathways using feature importance on echo state networks. CoRR Katherine Goode, Daniel Ries, Kellie McClernon
2023	J	`jnl`	Comparing the quality of neural network uncertainty estimates for classification problems. CoRR Daniel Ries, Joshua Michalenko, Tyler Ganter, Rashad Imad-Fayez Baiyasi, Jason Adams
2023	J	`jnl`	Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks. CoRR Daniel Ries, Jason Adams, Joshua Zollweg
2022	C	`conf`	Comparing the quality of neural network uncertainty estimates for classification problems. ICMLA Daniel Ries, Joshua Michalenko, Tyler Ganter, Rashad Imad-Fayez Baiyasi, Jason Adams
2021	—	`conf`	Hyperspectral Image Target Detection Using Deep Ensembles for Robust Uncertainty Quantification. ACSCC Rajeev Sahay, Daniel Ries, Joshua D. Zollweg, Christopher G. Brinton
2020	J	`jnl`	Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance. CoRR Katherine Goode, Daniel Ries, Joshua Zollweg