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Rich Caruana

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GAM Coach: Towards Interactive and User-centered Algorithmic Recourse

Mar 01, 2023
Zijie J. Wang, Jennifer Wortman Vaughan, Rich Caruana, Duen Horng Chau

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Estimating Discontinuous Time-Varying Risk Factors and Treatment Benefits for COVID-19 with Interpretable ML

Nov 15, 2022
Benjamin Lengerich, Mark E. Nunnally, Yin Aphinyanaphongs, Rich Caruana

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Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes

Jul 12, 2022
Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana

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Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values

Jun 30, 2022
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana

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Differentially Private Estimation of Heterogeneous Causal Effects

Feb 22, 2022
Fengshi Niu, Harsha Nori, Brian Quistorff, Rich Caruana, Donald Ngwe, Aadharsh Kannan

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GAM Changer: Editing Generalized Additive Models with Interactive Visualization

Dec 06, 2021
Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana

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Extracting Clinician's Goals by What-if Interpretable Modeling

Oct 28, 2021
Chun-Hao Chang, George Alexandru Adam, Rich Caruana, Anna Goldenberg

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Accuracy, Interpretability, and Differential Privacy via Explainable Boosting

Jun 17, 2021
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni

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NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning

Jun 03, 2021
Chun-Hao Chang, Rich Caruana, Anna Goldenberg

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Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models

Feb 09, 2021
Jonathan A. Weyn, Dale R. Durran, Rich Caruana, Nathaniel Cresswell-Clay

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