Torch-Choice: A PyTorch Package for Large-Scale Choice Modelling with Python
Tianyu Du, Ayush Kanodia, Susan Athey. April 2023 URL: https://arxiv.org/abs/2304.01906
Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning
Athey, Susan, Undral Byambadalai, Vitor Hadad, Sanath Kumar Krishnamurthy, Weiwen Leung, Joseph Jay Williams. arXiv preprint arXiv:2211:12004 (2022). URL: https://doi.org/10.48550/arXiv.2211.12004
CAREER: Transfer Learning for Economic Prediction of Labor Sequence Data
Keyon Vafa, Emil Palikot, Tianyu Du, Ayush Kanodia, Susan Athey, David M. Blei October 2022 PDF: https://www.gsb.stanford.edu/gsb-box/route-download/620742
Uncovering Interpretable Potential Confounders in Electronic Medical Records
Jiaming Zeng, Michael F. Gensheimer, Daniel L. Rubin, Susan Athey, Ross D. Shachter Nature Communications February 23, 2022 Vol. 13 URL: https://doi.org/10.1038/s41467-022-28546-8
Stable Learning Establishes Some Common Ground between Causal Inference and Machine Learning
Peng Cui, Susan Athey, Nature Machine Intelligence, February 2022 Vol. 4 Issue 2 Pages 110–115 URL: https://doi.org/10.1038/s42256-022-00445-z
Synthetic Difference-in-Differences
Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido W. Imbens, Stefan Wager. American Economic Review. December 2021 Vol. 111 Issue 12 Pages 4088–4118 URL: https://www.aeaweb.org/articles?id=10.1257/aer.20190159
Semiparametric Estimation of Treatment Effects in Randomized Experiments
Athey, Susan, Peter J. Bickel, Aiyou Chen, Guido Imbens, and Michael Pollmann. National Bureau of Economic Research Working Paper No. w29242. (2021) URL: https://www.nber.org/papers/w29242
Breiman’s Two Cultures – A Perspective from Econometrics
Guido Imbens Observational Studies, Volume 7, Issue 1, July 2021 July 2021 URL: https://muse.jhu.edu/article/799753
Federated Causal Inference in Heterogeneous Observational Data
Ruoxuan Xiong, Allison Koenecke, Michael Powell, Zhu Shen, Joshua T. Vogelstein arXiv:2107.11732 August 2021 URL: https://arxiv.org/abs/2107.11732
Integrating explanation and prediction in computational social science
Jake M. Hofman, Duncan J. Watts Nature (2021). https://doi.org/10.1038/s41586-021-03659-0. June 2021 URL: https://www.nature.com/articles/s41586-021-03659-0
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