Daniel Ries

According to our database, Daniel Ries authored at least 9 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Regression Recalibration by Learning PIT Map Values.

Christopher Qian, Daniel Ries, Feng Liang, Jason Adams

Technometrics, July, 2025

An Explainable Pipeline for Machine Learning with Functional Data.

Katherine Goode, J. Derek Tucker, Daniel Ries, Heike Hofmann

CoRR, January, 2025

Elastic Bayesian Model Calibration.

Devin Francom, J. Derek Tucker, Gabriel Huerta, Kurtis Shuler, Daniel Ries

SIAM/ASA J. Uncertain. Quantification, 2025

2024

Characterizing climate pathways using feature importance on echo state networks.

Katherine Goode, Daniel Ries, Kellie McClernon

Stat. Anal. Data Min., August, 2024

2023

A Framework for Inverse Prediction Using Functional Response Data.

Daniel Ries, Adah Zhang, J. Derek Tucker, Kurtis Shuler, Madeline Ausdemore

J. Comput. Inf. Sci. Eng., 2023

Target Detection on Hyperspectral Images Using MCMC and VI Trained Bayesian Neural Networks.

Daniel Ries, Jason Adams, Joshua Zollweg

CoRR, 2023

2022

Comparing the quality of neural network uncertainty estimates for classification problems.

Daniel Ries, Joshua Michalenko, Tyler Ganter, Rashad Imad-Fayez Baiyasi, Jason Adams

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2021

Hyperspectral Image Target Detection Using Deep Ensembles for Robust Uncertainty Quantification.

Rajeev Sahay, Daniel Ries, Joshua D. Zollweg, Christopher G. Brinton

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance.

Katherine Goode, Daniel Ries, Joshua Zollweg

CoRR, 2020