Large-scale text processing pipeline with Apache Spark. - Alexey Svyatkovskiy; Kosuke Imai; Mary Kroeger; Yuki Shiraito (IEEE BigData, 2016)

Keyword Assisted Topic Models. - Shusei Eshima; Kosuke Imai; Tomoya Sasaki (CoRR, 2020)

Principal Fairness for Human and Algorithmic Decision-Making. - Kosuke Imai; Zhichao Jiang (CoRR, 2020)

The Essential Role of Empirical Validation in Legislative Redistricting Simulation. - Benjamin Fifield; Kosuke Imai; Jun Kawahara; Christopher T. Kenny (CoRR, 2020)

Sequential Monte Carlo for Sampling Balanced and Compact Redistricting Plans. - Cory McCartan; Kosuke Imai (CoRR, 2020)

Experimental Evaluation of Algorithm-Assisted Human Decision-Making: Application to Pretrial Public Safety Assessment. - Kosuke Imai; Zhichao Jiang; James Greiner; Ryan Halen; Sooahn Shin (CoRR, 2020)

Dynamic Stochastic Blockmodel Regression for Network Data: Application to International Militarized Conflicts. - Santiago Olivella; Tyler Pratt; Kosuke Imai (CoRR, 2021)

The Impact of the U.S. Census Disclosure Avoidance System on Redistricting and Voting Rights Analysis. - Christopher T. Kenny; Shiro Kuriwaki; Cory McCartan; Evan Rosenman; Tyler Simko; Kosuke Imai (CoRR, 2021)

Safe Policy Learning through Extrapolation: Application to Pre-trial Risk Assessment. - Eli Ben-Michael; D. James Greiner; Kosuke Imai; Zhichao Jiang (CoRR, 2021)

Measuring and Modeling Neighborhoods. - Cory McCartan; Jacob R. Brown; Kosuke Imai (CoRR, 2021)

Causal Diagram and Social Science Research. - Kosuke Imai (Probabilistic and Causal Inference, 2022)

Addressing Census data problems in race imputation via fully Bayesian Improved Surname Geocoding and name supplements. - Kosuke Imai; Santiago Olivella; Evan T. R. Rosenman (CoRR, 2022)

Policy learning with asymmetric utilities. - Eli Ben-Michael; Kosuke Imai; Zhichao Jiang (CoRR, 2022)

Simulated redistricting plans for the analysis and evaluation of redistricting in the United States: 50stateSimulations. - Cory McCartan; Christopher T. Kenny; Tyler Simko; George Garcia III; Kevin Wang; Melissa Wu; Shiro Kuriwaki; Kosuke Imai (CoRR, 2022)

Race and ethnicity data for first, middle, and last names. - Evan T. R. Rosenman; Santiago Olivella; Kosuke Imai (CoRR, 2022)

Distributionally Robust Causal Inference with Observational Data. - Dimitris Bertsimas; Kosuke Imai; Michael Lingzhi Li (CoRR, 2022)

Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System. - Christopher T. Kenny; Shiro Kuriwaki; Cory McCartan; Evan T. R. Rosenman; Tyler Simko; Kosuke Imai (CoRR, 2022)

Estimating Racial Disparities When Race is Not Observed. - Cory McCartan; Jacob Goldin; Daniel E. Ho; Kosuke Imai (CoRR, 2023)

A Statistical Model of Bipartite Networks: Application to Cosponsorship in the United States Senate. - Adeline Lo; Santiago Olivella; Kosuke Imai (CoRR, 2023)

Making Differential Privacy Work for Census Data Users. - Cory McCartan; Tyler Simko; Kosuke Imai (CoRR, 2023)

Evaluating Bias and Noise Induced by the U.S. Census Bureau's Privacy Protection Methods. - Christopher T. Kenny; Shiro Kuriwaki; Cory McCartan; Tyler Simko; Kosuke Imai (CoRR, 2023)

Bayesian Safe Policy Learning with Chance Constrained Optimization: Application to Military Security Assessment during the Vietnam War. - Zeyang Jia; Eli Ben-Michael; Kosuke Imai (CoRR, 2023)

Individualized Policy Evaluation and Learning under Clustered Network Interference. - Yi Zhang; Kosuke Imai (CoRR, 2023)

The Cram Method for Efficient Simultaneous Learning and Evaluation. - Zeyang Jia; Kosuke Imai; Michael Lingzhi Li (CoRR, 2024)

Does AI help humans make better decisions? A methodological framework for experimental evaluation. - Eli Ben-Michael; D. James Greiner; Melody Huang; Kosuke Imai; Zhichao Jiang; Sooahn Shin (CoRR, 2024)

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules. - Michael Lingzhi Li; Kosuke Imai (CoRR, 2024)

Causal Representation Learning with Generative Artificial Intelligence: Application to Texts as Treatments. - Kosuke Imai; Kentaro Nakamura (CoRR, 2024)

Using AI to Summarize US Presidential Campaign TV Advertisement Videos, 1952-2012. - Adam Breuer; Bryce J. Dietrich; Michael H. Crespin; Matthew Butler 005; J. A. Pyrse; Kosuke Imai (CoRR, 2025)

Statistical Decision Theory with Counterfactual Loss. - Benedikt Koch; Kosuke Imai (CoRR, 2025)

GenAI-Powered Inference. - Kosuke Imai; Kentaro Nakamura (CoRR, 2025)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)