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Uncertainty Quantification 360: A Holistic Toolkit for Quantifying and Communicating the Uncertainty of AI


Jun 04, 2021
Soumya Ghosh, Q. Vera Liao, Karthikeyan Natesan Ramamurthy, Jiri Navratil, Prasanna Sattigeri, Kush R. Varshney, Yunfeng Zhang

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* Added references 

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Uncertainty Characteristics Curves: A Systematic Assessment of Prediction Intervals


Jun 01, 2021
Jiri Navratil, Benjamin Elder, Matthew Arnold, Soumya Ghosh, Prasanna Sattigeri

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* 10 pages main paper, 9 pages appendix 

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Learning Prediction Intervals for Model Performance


Dec 15, 2020
Benjamin Elder, Matthew Arnold, Anupama Murthi, Jiri Navratil

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* 7+6 pages, 5 figures, AAAI 2021 

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Not Your Grandfathers Test Set: Reducing Labeling Effort for Testing


Jul 10, 2020
Begum Taskazan, Jiri Navratil, Matthew Arnold, Anupama Murthi, Ganesh Venkataraman, Benjamin Elder

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* International Workshop on Challenges in Deploying and Monitoring Machine Learning Systems in Conjunction with ICML 2020 

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Uncertainty Prediction for Deep Sequential Regression Using Meta Models


Jul 02, 2020
Jiri Navratil, Matthew Arnold, Benjamin Elder

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* 8 pages main paper + 11 pages appendix/references; 10 figures 

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Towards Automating the AI Operations Lifecycle


Mar 28, 2020
Matthew Arnold, Jeffrey Boston, Michael Desmond, Evelyn Duesterwald, Benjamin Elder, Anupama Murthi, Jiri Navratil, Darrell Reimer

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Accelerating Physics-Based Simulations Using Neural Network Proxies: An Application in Oil Reservoir Modeling


May 23, 2019
Jiri Navratil, Alan King, Jesus Rios, Georgios Kollias, Ruben Torrado, Andres Codas

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* 9 pages, submitted to FEED-2019 KDD Workshop & Frontiers in Big Data 

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