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The MultiBERTs: BERT Reproductions for Robustness Analysis


Jun 30, 2021
Thibault Sellam, Steve Yadlowsky, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Turc, Jacob Eisenstein, Dipanjan Das, Ian Tenney, Ellie Pavlick

* Checkpoints and example analyses: http://goo.gle/multiberts 

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Causally-motivated Shortcut Removal Using Auxiliary Labels


Jun 03, 2021
Maggie Makar, Ben Packer, Dan Moldovan, Davis Blalock, Yoni Halpern, Alexander D'Amour


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Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests


Jun 02, 2021
Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein


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Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap


Apr 12, 2021
Alexander D'Amour, Alexander Franks

* A previous version of this paper was presented at the NeurIPS 2019 Causal ML workshop (https://tripods.cis.cornell.edu/neurips19_causalml/

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Revisiting Rashomon: A Comment on "The Two Cultures"


Apr 05, 2021
Alexander D'Amour

* Commentary to appear in a special issue of Observational Studies, discussing Leo Breiman's paper "Statistical Modeling: The Two Cultures" (https://doi.org/10.1214/ss/1009213726) and accompanying commentary 

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SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression


Mar 23, 2021
Steve Yadlowsky, Taedong Yun, Cory McLean, Alexander D'Amour


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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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Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift


Jul 17, 2020
Zachary Nado, Shreyas Padhy, D. Sculley, Alexander D'Amour, Balaji Lakshminarayanan, Jasper Snoek


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On Robustness and Transferability of Convolutional Neural Networks


Jul 16, 2020
Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvan Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic


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A Biologically Plausible Benchmark for Contextual Bandit Algorithms in Precision Oncology Using in vitro Data


Nov 11, 2019
Niklas T. Rindtorff, MingYu Lu, Nisarg A. Patel, Huahua Zheng, Alexander D'Amour

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

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Comment: Reflections on the Deconfounder


Oct 17, 2019
Alexander D'Amour

* Comment to appear in JASA discussion of "The Blessings of Multiple Causes." 

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On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives


Mar 19, 2019
Alexander D'Amour

* Accepted to AISTATS 2019. Since last revision: corrected constant factors in linear gaussian example; fixed typos 

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Reducing Reparameterization Gradient Variance


May 22, 2017
Andrew C. Miller, Nicholas J. Foti, Alexander D'Amour, Ryan P. Adams


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