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Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs


Feb 17, 2021
Harini Suresh, Kathleen M. Lewis, John V. Guttag, Arvind Satyanarayan


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Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings


Jan 04, 2020
Amy Zhao, Guha Balakrishnan, Kathleen M. Lewis, Frédo Durand, John V. Guttag, Adrian V. Dalca


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Visual Deprojection: Probabilistic Recovery of Collapsed Dimensions


Sep 01, 2019
Guha Balakrishnan, Adrian V. Dalca, Amy Zhao, John V. Guttag, Fredo Durand, William T. Freeman

* ICCV 2019 

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Data augmentation using learned transformations for one-shot medical image segmentation


Apr 06, 2019
Amy Zhao, Guha Balakrishnan, Frédo Durand, John V. Guttag, Adrian V. Dalca

* 9 pages, CVPR 2019 

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A Framework for Understanding Unintended Consequences of Machine Learning


Jan 28, 2019
Harini Suresh, John V. Guttag

* 6 pages, 2 figures 

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EXTRACT: Strong Examples from Weakly-Labeled Sensor Data


Sep 29, 2016
Davis W. Blalock, John V. Guttag

* To appear in IEEE International Conference on Data Mining 2016 

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Uncovering Voice Misuse Using Symbolic Mismatch


Aug 08, 2016
Marzyeh Ghassemi, Zeeshan Syed, Daryush D. Mehta, Jarrad H. Van Stan, Robert E. Hillman, John V. Guttag

* Presented at 2016 Machine Learning and Healthcare Conference (MLHC 2016), Los Angeles, CA 

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Transferring Knowledge from Text to Predict Disease Onset


Aug 06, 2016
Yun Liu, Kun-Ta Chuang, Fu-Wen Liang, Huey-Jen Su, Collin M. Stultz, John V. Guttag

* Presented at 2016 Machine Learning and Healthcare Conference (MLHC 2016), Los Angeles, CA 

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