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Publication	Type	Year
Robust Arrival Time Uncertainty Estimation Using Gaussian Blurring 2019 Seismological Society of America Annual Meeting Matthew Gregor Peterson, Charles Vollmer, David John Stracuzzi, Christopher J. Young	Abstract – 2019 Abstract	2019
Quantifying Uncertainty to Improve Decision Making in Machine Learning David John Stracuzzi, Michael Christopher Darling, Matthew Gregor Peterson, Maximillian Gene Chen https://www.osti.gov/search/identifier:1481629	SAND Report – 2018 SAND Report	2018
Dynamic Tuning of Seismic Signal Detector Bulletin of the Seismological Society of America Timothy J. Draelos, Matthew Gregor Peterson, Hunter Anne Knox, Benjamin J. Lawry, Kristin E. Phillips-Alonge, Abra E. Ziegler, Eric P. Chael, Christopher J. Young, Aleksandra Faust https://www.osti.gov/search/identifier:1469633	Journal Article – 2018 Journal Article	2018
Using Uncertainty to Understand Machine Learning Models and Decisions Research Challenges and Opportunities at the interface of Machine Learning and Uncertainty Quantification Maximillian Gene Chen, Michael Christopher Darling, Charles Vollmer, Matthew Gregor Peterson, David John Stracuzzi https://www.osti.gov/search/identifier:1526113	Conference Paper – 2018 Conference Paper	2018
Data-Driven Uncertainty Quantification for Multisensor Analytics SPIE Defense+Security David John Stracuzzi, Michael Christopher Darling, Maximillian Gene Chen, Matthew Gregor Peterson https://www.osti.gov/search/identifier:1575173	Conference Paper – 2018 Conference Paper	2018
Data-Driven Uncertainty Quantification for Multi-Sensor Analytics SPIE Defense + Security David John Stracuzzi, Michael Christopher Darling, Maximillian Gene Chen, Matthew Gregor Peterson https://www.osti.gov/search/identifier:1507484	Conference Paper – 2018 Conference Paper	2018
UQ Pipeline for Seismic Onset Detection Conference on Data Analysis (CoDA) Matthew Gregor Peterson, David John Stracuzzi https://www.osti.gov/search/identifier:1497535	Conference Paper – 2018 Conference Paper	2018
CoDA Poster Abstract Conference on Data Analysis Matthew Gregor Peterson, David John Stracuzzi	Abstract – 2018 Abstract	2018
Arctic Tipping Points Triggering Global Change Geoscience External Advisory Board Meeting Kara J. Peterson, Michael L. Parks, Eric Ackerman, Ray Bambha, Diana L Bull, Jennifer M Frederick, Jasper O. E. Hardesty, Anastasia Gennadyevna Ilgen, John Davis Jakeman, Amy Jo Powell, Matthew Gregor Peterson, Erika Louise Roesler, Cosmin Safta, David John Stracuzzi, Irina Kalashnikova Tezaur https://www.osti.gov/search/identifier:1513640	Conference Paper – 2018 Conference Paper	2018
From Data to Decisions: Placing Machine Learning Challenges In Context Neural Information Processing Systems Workshop on Challenges in Machine Learning David John Stracuzzi, Maximillian Gene Chen, Michael Christopher Darling, Matthew Gregor Peterson https://www.osti.gov/search/identifier:1484938	Conference Paper – 2017 Conference Paper	2017
Arctic Tipping Points Triggering Global Change Geoscience External Review Board Kara J. Peterson, Michael L. Parks, Eric Ackerman, Ray Bambha, Diana L Bull, Jennifer M Frederick, Jasper O. E. Hardesty, Anastasia Gennadyevna Ilgen, John Davis Jakeman, Matthew Gregor Peterson, Amy Jo Powell, Erika Louise Roesler, Cosmin Safta, David John Stracuzzi, Irina Kalashnikova Tezaur	Display or Poster (non-conference) – 2017 Display or Poster (non-conference)	2017
Establishing Uniform Image Segmentation Ground Truth Protocols for Uncertainty Quantification and Improved Model Evaluation Machine Learning Challenges as a Research Tool Maximillian Gene Chen, David John Stracuzzi, Michael Christopher Darling, Matthew Gregor Peterson https://www.osti.gov/search/identifier:1511807	Conference Paper – 2017 Conference Paper	2017
Change Point Uncertainty Quantification: First Arrival Picks for Seismic Signals Nips WorkshopTime Series Analysis Matthew Gregor Peterson, David John Stracuzzi, Charles Vollmer https://www.osti.gov/search/identifier:1481487	Conference Paper – 2017 Conference Paper	2017
Uncertainty Quantification for Seismic Events Super Computing Matthew Gregor Peterson https://www.osti.gov/search/identifier:1480654	Conference Paper – 2017 Conference Paper	2017
Data-Driven Uncertainty Quantification for Multi-Sensor Analytics SPIE Defense and Security Conference David John Stracuzzi, Maximillian Gene Chen, Michael Christopher Darling, Matthew Gregor Peterson	Abstract – 2017 Abstract	2017
Establishing Uniform Image Segmentation Ground Truth Protocols for Uncertainty Quantification and Improved Model Evaluation Challenges in Machine Learning 2017 Maximillian Gene Chen, David John Stracuzzi, Michael Christopher Darling, Matthew Gregor Peterson	Abstract – 2017 Abstract	2017
Increasing Trust By Quantifying Uncertainty Trustworthy Algorithmic Decision-Making Michael Christopher Darling, David John Stracuzzi, Matthew Gregor Peterson, Maximillian Gene Chen, Michael Christopher Darling, Michael Christopher Darling	Abstract – 2017 Abstract	2017
From Data to Decisions: Placing Machine Learning Challenges in Context NIPS 2017 WorkshopMachine Learning Challenges as a Research Tool David John Stracuzzi, Maximillian Gene Chen, Michael Christopher Darling, Matthew Gregor Peterson	Abstract – 2017 Abstract	2017
Adaptive Self-Tuning of Signal Detection Parameters Timothy J. Draelos, Matthew Gregor Peterson, Hunter Anne Knox, Benjamin James Lawry, Kristin Philips-Alonge, Abra Ziegler, Eric Chael, Christopher J. Young, Aleksandra Faust https://www.osti.gov/search/identifier:1596198	SAND Report – 2017 SAND Report	2017
Using Data-Driven Uncertainty Quantification to Support Decision Making Cis Rf Erb David John Stracuzzi, Matthew Gregor Peterson, Charles Vollmer https://www.osti.gov/search/identifier:1465020	Display or Poster (non-conference) – 2017 Display or Poster (non-conference)	2017
Experiments on Adaptive Self-Tuning of Seismic Signal Detector Parameters American Geophysical Union Hunter Anne Knox, Timothy J. Draelos, Christopher J. Young, Matthew Gregor Peterson, Kristin (DTRA) Phillips-Allonge, Robert (NMT) Balch, Abra Elizabeth Ziegler https://www.osti.gov/search/identifier:1431965	Conference Paper – 2017 Conference Paper	2017
Automated Sensor Tuning for Seismic Event Detection at a Carbon Capture, Utilization, and Storage Site, Farnsworth Unit, Ochiltree County, Texas American Geophysical Union Abra Elizabeth Ziegler, Robert (NMT) Balch, Hunter Anne Knox, Jolante (NMT) van Wijk, Timothy J. Draelos, Matthew Gregor Peterson https://www.osti.gov/search/identifier:1431964	Conference Paper – 2017 Conference Paper	2017
Evaluation Of Adaptive Sensor Tuning For Microseismic Event Detection In Varying Noise Conditions At A Carbon Capture, Utilization, And Storage Site Ssa 2017 Abra Elizabeth Ziegler, Robert Balch, Hunter Anne Knox, Jolante Van Wijk, Timothy J. Draelos, Matthew Gregor Peterson https://www.osti.gov/search/identifier:1513619	Conference Paper – 2017 Conference Paper	2017
Uncertainty Quantification for Machine Learning David John Stracuzzi, Maximillian Gene Chen, Michael Christopher Darling, Matthew Gregor Peterson, Charles Vollmer https://www.osti.gov/search/identifier:1733262	SAND Report – 2017 SAND Report	2017
Using Data-Driven Uncertainty Quantification to Support Decision Making Statistical Data Science Conference Charles Vollmer, Matthew Gregor Peterson, David John Stracuzzi, Maximillian Gene Chen https://www.osti.gov/search/identifier:1513614	Conference Paper – 2017 Conference Paper	2017
Document Title	Type	Year

Results 26–50 of 71

Publications

Robust Arrival Time Uncertainty Estimation Using Gaussian Blurring

Quantifying Uncertainty to Improve Decision Making in Machine Learning

Dynamic Tuning of Seismic Signal Detector

Using Uncertainty to Understand Machine Learning Models and Decisions

Data-Driven Uncertainty Quantification for Multisensor Analytics

Data-Driven Uncertainty Quantification for Multi-Sensor Analytics

UQ Pipeline for Seismic Onset Detection

CoDA Poster Abstract

Arctic Tipping Points Triggering Global Change

From Data to Decisions: Placing Machine Learning Challenges In Context

Arctic Tipping Points Triggering Global Change

Establishing Uniform Image Segmentation Ground Truth Protocols for Uncertainty Quantification and Improved Model Evaluation

Change Point Uncertainty Quantification: First Arrival Picks for Seismic Signals

Uncertainty Quantification for Seismic Events

Data-Driven Uncertainty Quantification for Multi-Sensor Analytics

Establishing Uniform Image Segmentation Ground Truth Protocols for Uncertainty Quantification and Improved Model Evaluation

Increasing Trust By Quantifying Uncertainty

From Data to Decisions: Placing Machine Learning Challenges in Context

Adaptive Self-Tuning of Signal Detection Parameters

Using Data-Driven Uncertainty Quantification to Support Decision Making

Experiments on Adaptive Self-Tuning of Seismic Signal Detector Parameters

Automated Sensor Tuning for Seismic Event Detection at a Carbon Capture, Utilization, and Storage Site, Farnsworth Unit, Ochiltree County, Texas

Evaluation Of Adaptive Sensor Tuning For Microseismic Event Detection In Varying Noise Conditions At A Carbon Capture, Utilization, And Storage Site

Uncertainty Quantification for Machine Learning

Using Data-Driven Uncertainty Quantification to Support Decision Making