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Evaluation Gaps in Machine Learning Practice


May 11, 2022
Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine Heller, Vinodkumar Prabhakaran


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Disability prediction in multiple sclerosis using performance outcome measures and demographic data


Apr 08, 2022
Subhrajit Roy, Diana Mincu, Lev Proleev, Negar Rostamzadeh, Chintan Ghate, Natalie Harris, Christina Chen, Jessica Schrouff, Nenad Tomasev, Fletcher Lee Hartsell, Katherine Heller


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Healthsheet: Development of a Transparency Artifact for Health Datasets


Feb 26, 2022
Negar Rostamzadeh, Diana Mincu, Subhrajit Roy, Andrew Smart, Lauren Wilcox, Mahima Pushkarna, Jessica Schrouff, Razvan Amironesei, Nyalleng Moorosi, Katherine Heller


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Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?


Feb 02, 2022
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alex Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine Heller, Silvia Chiappa, Alexander D'Amour


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Deep Cox Mixtures for Survival Regression


Jan 16, 2021
Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine Heller

* NeurIPS Machine Learning for Health Workshop (ML4H) 2020 

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Underspecification Presents Challenges for Credibility in Modern Machine Learning


Nov 06, 2020
Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley


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Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors


May 14, 2020
Michael W. Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-an Ma, Jasper Snoek, Katherine Heller, Balaji Lakshminarayanan, Dustin Tran

* Code available at https://github.com/google/edward2 

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Federated and Differentially Private Learning for Electronic Health Records


Nov 13, 2019
Stephen R. Pfohl, Andrew M. Dai, Katherine Heller

* Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended Abstract 

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Analyzing the Role of Model Uncertainty for Electronic Health Records


Jun 10, 2019
Michael W. Dusenberry, Dustin Tran, Edward Choi, Jonas Kemp, Jeremy Nixon, Ghassen Jerfel, Katherine Heller, Andrew M. Dai

* Presented at the ICML 2019 Workshop on Uncertainty & Robustness in Deep Learning. Code to be open-sourced 

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Online gradient-based mixtures for transfer modulation in meta-learning


Dec 17, 2018
Ghassen Jerfel, Erin Grant, Thomas L. Griffiths, Katherine Heller


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