A Comparison of the Fortune 500 and AACSB Accredited Universities' Software Copying Policies. - Susan Athey (J. Inf. Syst. Educ., 1990)

Where have all the women gone? - Susan Athey; John A. Hoxmeier (IRMA Conference, 2000)

An Evaluation of Research Productivity in Academic IT. - Susan Athey; John Plotnicki (Commun. Assoc. Inf. Syst., 2000)

Programming Standards for the Information Systems Curriculum. - Julie Tomlin; John A. Hoxmeier; Susan Athey (AMCIS, 2007)

Designing markets: economics, computer science and the real world. - Susan Athey (TARK, 2009)

Use of the World Wide Web by the Portuguese Accommodation Industry. - Susan Athey (J. Inf. Technol. Tour., 2011)

Machine Learning and Causal Inference for Policy Evaluation. - Susan Athey (KDD, 2015)

Context Selection for Embedding Models. - Li-Ping Liu 001; Francisco J. R. Ruiz; Susan Athey; David M. Blei (NIPS, 2017)

Structured Embedding Models for Grouped Data. - Maja Rudolph; Francisco J. R. Ruiz; Susan Athey; David M. Blei (NIPS, 2017)

Efficient Policy Learning. - Susan Athey; Stefan Wager (CoRR, 2017)

SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements. - Francisco J. R. Ruiz; Susan Athey; David M. Blei (CoRR, 2017)

Estimation Considerations in Contextual Bandits. - Maria Dimakopoulou; Susan Athey; Guido Imbens (CoRR, 2017)

Stable Prediction across Unknown Environments. - Kun Kuang; Peng Cui 001; Susan Athey; Ruoxuan Xiong; Bo Li 064 (KDD, 2018)

Learning in Games with Lossy Feedback. - Zhengyuan Zhou; Panayotis Mertikopoulos; Susan Athey; Nicholas Bambos; Peter W. Glynn; Yinyu Ye 001 (NeurIPS, 2018)

Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data. - Susan Athey; David M. Blei; Robert Donnelly; Francisco J. R. Ruiz; Tobias Schmidt (CoRR, 2018)

Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption. - Susan Athey; Guido Imbens (CoRR, 2018)

The Impact of Consumer Multi-homing on Advertising Markets and Media Competition. - Susan Athey; Emilio Calvano; Joshua S. Gans (Manag. Sci., 2018)

Balanced Linear Contextual Bandits. - Maria Dimakopoulou; Zhengyuan Zhou; Susan Athey; Guido Imbens (AAAI, 2019)

Counterfactual Inference for Consumer Choice Across Many Product Categories. - Robert Donnelly; Francisco J. R. Ruiz; David M. Blei; Susan Athey (CoRR, 2019)

Sufficient Representations for Categorical Variables. - Jonathan Johannemann; Vitor Hadad; Susan Athey; Stefan Wager (CoRR, 2019)

Confidence Intervals for Policy Evaluation in Adaptive Experiments. - Vitor Hadad; David A. Hirshberg; Ruohan Zhan; Stefan Wager; Susan Athey (CoRR, 2019)

Stable Prediction with Model Misspecification and Agnostic Distribution Shift. - Kun Kuang; Ruoxuan Xiong; Peng Cui 001; Susan Athey; Bo Li 064 (AAAI, 2020)

Survey Bandits with Regret Guarantees. - Sanath Kumar Krishnamurthy; Susan Athey (CoRR, 2020)

Peaches, lemons, and cookies: Designing auction markets with dispersed information. - Ittai Abraham; Susan Athey; Moshe Babaioff; Michael Grubb (Games Econ. Behav., 2020)

policytree: Policy learning via doubly robust empirical welfare maximization over trees. - Erik Sverdrup; Ayush Kanodia; Zhengyuan Zhou; Susan Athey; Stefan Wager (J. Open Source Softw., 2020)

Tractable contextual bandits beyond realizability. - Sanath Kumar Krishnamurthy; Vitor Hadad; Susan Athey (AISTATS, 2021)

Adapting to misspecification in contextual bandits with offline regression oracles. - Sanath Kumar Krishnamurthy; Vitor Hadad; Susan Athey (ICML, 2021)

Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits. - Ruohan Zhan; Vitor Hadad; David A. Hirshberg; Susan Athey (KDD, 2021)

Optimal Model Selection in Contextual Bandits with Many Classes via Offline Oracles. - Sanath Kumar Krishnamurthy; Susan Athey (CoRR, 2021)

Federated Causal Inference in Heterogeneous Observational Data. - Ruoxuan Xiong; Allison Koenecke; Michael A. Powell; Zhu Shen; Joshua T. Vogelstein; Susan Athey (CoRR, 2021)

Local Linear Forests. - Rina Friedberg; Julie Tibshirani; Susan Athey; Stefan Wager (J. Comput. Graph. Stat., 2021)

Learning Transferrable Representations of Career Trajectories for Economic Prediction. - Keyon Vafa; Emil Palikot; Tianyu Du; Ayush Kanodia; Susan Athey; David M. Blei (CoRR, 2022)

Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracle. - Aldo Gael Carranza; Sanath Kumar Krishnamurthy; Susan Athey (CoRR, 2022)

Contextual Bandits in a Survey Experiment on Charitable Giving: Within-Experiment Outcomes versus Policy Learning. - Susan Athey; Undral Byambadalai; Vitor Hadad; Sanath Kumar Krishnamurthy; Weiwen Leung; Joseph Jay Williams (CoRR, 2022)

Battling the Coronavirus 'Infodemic' Among Social Media Users in Africa. - Molly Offer-Westort; Leah R. Rosenzweig; Susan Athey (CoRR, 2022)

Stable learning establishes some common ground between causal inference and machine learning. - Peng Cui 001; Susan Athey (Nat. Mach. Intell., 2022)

Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles. - Aldo Gael Carranza; Sanath Kumar Krishnamurthy; Susan Athey (AISTATS, 2023)

Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization. - Sanath Kumar Krishnamurthy; Ruohan Zhan; Susan Athey; Emma Brunskill (NeurIPS, 2023)

Torch-Choice: A PyTorch Package for Large-Scale Choice Modelling with Python. - Tianyu Du; Ayush Kanodia; Susan Athey (CoRR, 2023)

Federated Offline Policy Learning with Heterogeneous Observational Data. - Aldo Gael Carranza; Susan Athey (CoRR, 2023)

Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal. - Susan Athey; Niall Keleher; Jann Spiess (CoRR, 2023)

Offline Multi-Action Policy Learning: Generalization and Optimization. - Zhengyuan Zhou; Susan Athey; Stefan Wager (Oper. Res., 2023)

Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective. - Sanath Kumar Krishnamurthy; Adrienne Margaret Propp; Susan Athey (AISTATS, 2024)

Data-driven Error Estimation: Upper Bounding Multiple Errors with No Technical Debt. - Sanath Kumar Krishnamurthy; Susan Athey; Emma Brunskill (CoRR, 2024)

LABOR-LLM: Language-Based Occupational Representations with Large Language Models. - Tianyu Du; Ayush Kanodia; Herman Brunborg; Keyon Vafa; Susan Athey (CoRR, 2024)

Estimating Wage Disparities Using Foundation Models. - Keyon Vafa; Susan Athey; David M. Blei (CoRR, 2024)

Optimal Experimental Design for Staggered Rollouts. - Ruoxuan Xiong; Susan Athey; Mohsen Bayati; Guido Imbens (Manag. Sci., 2024)

Policy Learning with Adaptively Collected Data. - Ruohan Zhan; Zhimei Ren; Susan Athey; Zhengyuan Zhou (Manag. Sci., 2024)

CAREER: A Foundation Model for Labor Sequence Data. - Keyon Vafa; Emil Palikot; Tianyu Du; Ayush Kanodia; Susan Athey; David M. Blei (Trans. Mach. Learn. Res., 2024)

Robust Offline Policy Learning with Observational Data from Multiple Sources. - Aldo Gael Carranza; Susan Athey (AISTATS, 2025)

Identification of Average Treatment Effects in Nonparametric Panel Models. - Susan Athey; Guido Imbens (CoRR, 2025)