Search Results - "D’Amour, Alexander"

Disambiguation and co-authorship networks of the U.S. patent inventor database (1975–2010) by Li, Guan-Cheng, Lai, Ronald, D’Amour, Alexander, Doolin, David M., Sun, Ye, Torvik, Vetle I., Yu, Amy Z., Fleming, Lee

“…•An application of the Author-ity disambiguation approach (Torvik et al., 2005; Torvik and Smalheiser, 2009) to the US utility patent database.•A new iterative…”
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Statistical Deconvolution for Inference of Infection Time Series by Miller, Andrew C., Hannah, Lauren A., Futoma, Joseph, Foti, Nicholas J., Fox, Emily B., D’Amour, Alexander, Sandler, Mark, Saurous, Rif A., Lewnard, Joseph A.

“…Accurate measurement of daily infection incidence is crucial to epidemic response. However, delays in symptom onset, testing, and reporting obscure the…”
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Estimating Rates of Carriage Acquisition and Clearance and Competitive Ability for Pneumococcal Serotypes in Kenya With a Markov Transition Model by Lipsitch, Marc, Abdullahi, Osman, D'Amour, Alexander, Xie, Wen, Weinberger, Daniel M., Tchetgen, Eric Tchetgen, Scott, J. Anthony G.

“…Background: There are more than 90 serotypes of Streptococcus pneumoniae, with varying biologic and epidemiologic properties. Animal studies suggest that…”
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Comment: Reflections on the Deconfounder by D'Amour, Alexander

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Flexible Sensitivity Analysis for Observational Studies Without Observable Implications by Franks, AlexanderM, D'Amour, Alexander, Feller, Avi

“…A fundamental challenge in observational causal inference is that assumptions about unconfoundedness are not testable from data. Assessing sensitivity to such…”
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An intentional approach to managing bias in general purpose embedding models by Weng, Wei-Hung, Sellergen, Andrew, Kiraly, Atilla P, D'Amour, Alexander, Park, Jungyeon, Pilgrim, Rory, Pfohl, Stephen, Lau, Charles, Natarajan, Vivek, Azizi, Shekoofeh, Karthikesalingam, Alan, Cole-Lewis, Heather, Matias, Yossi, Corrado, Greg S, Webster, Dale R, Shetty, Shravya, Prabhakara, Shruthi, Eswaran, Krish, Celi, Leo A G, Liu, Yun

“…Advances in machine learning for health care have brought concerns about bias from the research community; specifically, the introduction, perpetuation, or…”
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Overlap in observational studies with high-dimensional covariates by D’Amour, Alexander, Ding, Peng, Feller, Avi, Lei, Lihua, Sekhon, Jasjeet

“…Estimating causal effects under exogeneity hinges on two key assumptions: unconfoundedness and overlap. Researchers often argue that unconfoundedness is more…”
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Sensitivity to Unobserved Confounding in Studies with Factor-Structured Outcomes by Zheng, Jiajing, Wu, Jiaxi, D'Amour, Alexander, Franks, Alexander

“…In this work, we propose an approach for assessing sensitivity to unobserved confounding in studies with multiple outcomes. We demonstrate how prior knowledge…”
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Revisiting Rashomon: A Comment on 'The Two Cultures' by D'Amour, Alexander

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Algorithmic Fairness: Choices, Assumptions, and Definitions by Mitchell, Shira, Potash, Eric, Barocas, Solon, D'Amour, Alexander, Lum, Kristian

“…A recent wave of research has attempted to define fairness quantitatively. In particular, this work has explored what fairness might mean in the context of…”
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Explaining and predicting the impact of authors within a community: an assessment of the bibliometric literature and application of machine learning by Chai, Sen, D’Amour, Alexander, Fleming, Lee

“…Abstract Following widespread availability of computerized databases, much research has correlated bibliometric measures from papers or patents to subsequent…”
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On Robustness and Transferability of Convolutional Neural Networks by Djolonga, Josip, Yung, Jessica, Tschannen, Michael, Romijnders, Rob, Beyer, Lucas, Kolesnikov, Alexander, Puigcerver, Joan, Minderer, Matthias, D'Amour, Alexander, Moldovan, Dan, Gelly, Sylvain, Houlsby, Neil, Zhai, Xiaohua, Lucic, Mario

“…Modern deep convolutional networks (CNNs) are often criticized for not generalizing under distributional shifts. However, several recent breakthroughs in…”
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Revisiting Rashomon: A Comment on "The Two Cultures" by D'Amour, Alexander

“…Here, I provide some reflections on Prof. Leo Breiman's "The Two Cultures" paper. I focus specifically on the phenomenon that Breiman dubbed the "Rashomon…”
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Comment: Reflections on the Deconfounder by D'Amour, Alexander

“…The aim of this comment (set to appear in a formal discussion in JASA) is to draw out some conclusions from an extended back-and-forth I have had with Wang and…”
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Fairness and robustness in anti-causal prediction by Makar, Maggie, D'Amour, Alexander

“…Published in TMLR, 2022 Robustness to distribution shift and fairness have independently emerged as two important desiderata required of modern machine…”
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On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives by D'Amour, Alexander

“…Unobserved confounding is a central barrier to drawing causal inferences from observational data. Several authors have recently proposed that this barrier can…”
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Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap by D'Amour, Alexander, Franks, Alexander

“…A key condition for obtaining reliable estimates of the causal effect of a treatment is overlap (a.k.a. positivity): the distributions of the features used to…”
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Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation by Lum, Kristian, Anthis, Jacy Reese, Nagpal, Chirag, D'Amour, Alexander

“…Bias benchmarks are a popular method for studying the negative impacts of bias in LLMs, yet there has been little empirical investigation of whether these…”
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Choosing a Proxy Metric from Past Experiments by Tripuraneni, Nilesh, Richardson, Lee, D'Amour, Alexander, Soriano, Jacopo, Yadlowsky, Steve

“…In many randomized experiments, the treatment effect of the long-term metric (i.e. the primary outcome of interest) is often difficult or infeasible to…”
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Bayesian Inference and Partial Identification in Multi-Treatment Causal Inference with Unobserved Confounding by Zheng, Jiajing, D'Amour, Alexander, Franks, Alexander

“…In causal estimation problems, the parameter of interest is often only partially identified, implying that the parameter cannot be recovered exactly, even with…”
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