Papers

Recent preprints and papers from the group, pulled automatically from arXiv. Last updated September 01, 2026.

• Aug 15, 2026

  Outcome Modeling in Design-Based Inference for Spatial Settings

  Arisa Sadeghpour, Erin Hartman

  arXiv:2608.15439 PDF stat.ME stat.AP
• Aug 04, 2026

  Confidence Horizons

  Chase Mathis, Ian Waudby-Smith

  arXiv:2608.03889 PDF stat.ME math.ST stat.ML
• Jul 30, 2026

  Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches

  Laura B. Balzer, Lei Nie, Issa J. Dahabreh, Kajsa Kvist, Tianyue Zhou, Demissie Alemayehu, Larry Han, Zhiwei Zhang, et al.

  arXiv:2607.27542 PDF stat.ME
• Jul 21, 2026

  Gaffke's confidence interval for the mean of bounded data is inadmissible but asymptotically efficient

  Jiahao Ming, Aaditya Ramdas, Yi Shen, Ruodu Wang, Ian Waudby-Smith

  arXiv:2607.18661 PDF math.ST cs.IT eess.SP
• Jul 21, 2026

  Robust Signal Maximization in Spillover Experiments

  Kirill Borusyak, Peter Hull, Evan Munro

  arXiv:2607.18601 PDF econ.EM
• Jul 10, 2026

  Misspecified regressions with mixed regressors: robust inference and causal interpretation

  Mengsi Gao, Peng Ding

  arXiv:2607.09536 PDF math.ST econ.EM stat.ME
• Jun 24, 2026

  Bridging Predictions and Interventions: An Integrated Framework for Automated Decision-Systems

  Inioluwa Deborah Raji, Lydia T. Liu, Angela Zhou, Luke Guerdan, Jessica Hullman, Daniel Malinsky, Bryan Wilder, Simone Zhang, Amanda Coston, Ezinne Nwankwo, Eli Ben-Michael, Avi Feller, et al.

  arXiv:2606.25668 PDF cs.CY
• Jun 12, 2026

  Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias

  Annie Ulichney, Amanda Coston

  arXiv:2606.14506 PDF stat.ML cs.LG stat.ME
• Jun 10, 2026

  Introducing the CP-plot for Causal Inference with Observational Studies

  Pengfei Tian, Fan Yang, Peng Ding

  arXiv:2606.11715 PDF stat.ME
• Jun 07, 2026

  AI-Assisted Variance Reduction in Randomized Experiments

  David Arbour, Eli Ben-Michael, Avi Feller, Apoorva Lal, Lo-Hua Yuan

  arXiv:2606.08853 PDF econ.EM stat.ME
• Jun 02, 2026

  Locally Equivalent Weights for Multilevel Regression and Poststratification

  Ryan Giordano, Alice Cima, Jared Murray, Erin Hartman, Avi Feller

  arXiv:2606.04250 PDF stat.ME
• Apr 21, 2026

  Auditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction

  Xiao Qi Lee, Ezinne Nwankwo, Angela Zhou

  arXiv:2604.19204 PDF cs.CY cs.LG
• Apr 20, 2026

  Improving reproducibility by controlling random seed stability in machine learning based estimation via bagging

  Nicholas Williams, Alejandro Schuler

  arXiv:2604.17694 PDF stat.ME cs.LG stat.ML
• Mar 20, 2026

  Estimating within-cluster and between-cluster spillover effects in randomized saturation designs

  Sizhu Lu, Lei Shi, Peng Ding

  arXiv:2603.19573 PDF stat.ME
• Mar 18, 2026

  Highly Adaptive Empirical Risk Minimization with Principal Components

  Carlos García Meixide, Mingxun Wang, Alejandro Schuler, Mark J. van der Laan

  arXiv:2603.18204 PDF math.ST
• Mar 18, 2026

  Multi-Armed Sequential Hypothesis Testing by Betting

  Ricardo J. Sandoval, Ian Waudby-Smith, Michael I. Jordan

  arXiv:2603.17925 PDF stat.ME cs.LG math.ST
• Mar 11, 2026

  Combining e-values using demi-supermartingales

  Jiahao Ming, Aaditya Ramdas, Yi Shen, Ruodu Wang, Ian Waudby-Smith

  arXiv:2603.10329 PDF stat.ME math.PR
• Mar 09, 2026

  Post-Hoc Large-Sample Statistical Inference

  Ben Chugg, Etienne Gauthier, Michael I. Jordan, Aaditya Ramdas, Ian Waudby-Smith

  arXiv:2603.08002 PDF math.ST stat.ME
• Feb 24, 2026

  Discussion of "Matrix Completion When Missing Is Not at Random and Its Applications in Causal Panel Data Models"

  Eli Ben-Michael, Avi Feller

  arXiv:2602.21314 PDF stat.ME
• Feb 19, 2026

  Generative modeling for the bootstrap

  Leon Tran, Ting Ye, Peng Ding, Fang Han

  arXiv:2602.17052 PDF stat.ME econ.EM
• Feb 18, 2026

  Introducing the b-value: combining unbiased and biased estimators from a sensitivity analysis perspective

  Zhexiao Lin, Peter J. Bickel, Peng Ding

  arXiv:2602.16310 PDF stat.ME econ.EM math.ST
• Feb 11, 2026

  Highly Adaptive Principal Component Regression

  Mingxun Wang, Alejandro Schuler, Mark van der Laan, Carlos García Meixide

  arXiv:2602.10613 PDF stat.ML cs.LG
• Feb 04, 2026

  A Weighting Framework for Clusters as Confounders in Observational Studies

  Eli Ben-Michael, Avi Feller, Luke Keele

  arXiv:2602.05041 PDF stat.ME
• Jan 27, 2026

  Decoupling and randomization for double-indexed permutation statistics

  Mingxuan Zou, Jingfan Xu, Peng Ding, Fang Han

  arXiv:2601.20018 PDF math.ST econ.EM math.PR
• Jan 23, 2026

  Falsifying Discriminant Validity of Predictive Algorithms

  Amanda Coston

  arXiv:2601.17146 PDF stat.ME cs.CY cs.LG
• Jan 21, 2026

  Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?

  Felix Schur, Niklas Pfister, Peng Ding, Sach Mukherjee, Jonas Peters

  arXiv:2601.15254 PDF stat.ML cs.AI cs.LG
• Jan 20, 2026

  Two-stage Least Squares with Clustered Data under the Local Average Treatment Effect Framework

  Anqi Zhao, Peng Ding, Fan Li

  arXiv:2601.13507 PDF stat.ME
• Jan 16, 2026

  On Nonasymptotic Confidence Intervals for Treatment Effects in Randomized Experiments

  Ricardo J. Sandoval, Sivaraman Balakrishnan, Avi Feller, Michael I. Jordan, Ian Waudby-Smith

  arXiv:2601.11744 PDF stat.ME math.ST stat.AP
• Dec 29, 2025

  Nonparametric Identification of Demand without Exogenous Product Characteristics

  Kirill Borusyak, Jiafeng Chen, Peter Hull, Lihua Lei

  arXiv:2512.23211 PDF econ.EM math.ST stat.ME
• Dec 15, 2025

  Machine learning to optimize precision in the analysis of randomized trials: A journey in pre-specified, yet data-adaptive learning

  Laura B. Balzer, Mark J. van der Laan, Maya L. Petersen

  arXiv:2512.13610 PDF stat.ME stat.ML
• Dec 12, 2025

  Forest Kernel Balancing Weights: Outcome-Guided Features for Causal Inference

  Andy A. Shen, Eli Ben-Michael, Avi Feller, Luke Keele, Jared Murray

  arXiv:2512.11751 PDF stat.ME stat.AP
• Nov 12, 2025

  Principled analysis of crossover designs: causal effects, efficient estimation, and robust inference

  Zhichao Jiang, Peng Ding

  arXiv:2511.09215 PDF stat.ME
• Oct 31, 2025

  Concentration inequalities for strong laws and laws of the iterated logarithm

  Johannes Ruf, Ian Waudby-Smith

  arXiv:2511.00175 PDF math.PR math.ST
• Oct 26, 2025

  Unifying regression-based and design-based causal inference in time-series experiments

  Zhexiao Lin, Peng Ding

  arXiv:2510.22864 PDF stat.ME econ.EM math.ST
• Oct 25, 2025

  TERRA: A Transformer-Enabled Recursive R-learner for Longitudinal Heterogeneous Treatment Effect Estimation

  Lei Shi, Sizhu Lu, Qiuran Lyu, Peng Ding, Nikos Vlassis

  arXiv:2510.22407 PDF stat.ME
• Oct 24, 2025

  Ridge Boosting is Both Robust and Efficient

  David Bruns-Smith, Zhongming Xie, Avi Feller

  arXiv:2510.22083 PDF stat.ME
• Oct 23, 2025

  Leveraging semantic similarity for experimentation with AI-generated treatments

  Lei Shi, David Arbour, Raghavendra Addanki, Ritwik Sinha, Avi Feller

  arXiv:2510.21119 PDF stat.ME stat.ML 62K86, 65F55
• Oct 23, 2025

  Handling Missing Responses under Cluster Dependence with Applications to Language Model Evaluation

  Zhenghao Zeng, David Arbour, Avi Feller, Ishita Dasgupta, Atanu R Sinha, Edward H. Kennedy

  arXiv:2510.20928 PDF stat.ME
• Sep 21, 2025

  Regularizing Extrapolation in Causal Inference

  David Arbour, Harsh Parikh, Bijan Niknam, Elizabeth Stuart, Kara Rudolph, Avi Feller

  arXiv:2509.17180 PDF cs.LG econ.EM stat.ME
• Sep 16, 2025

  Inverse regression for causal inference with multiple outcomes

  Wei Zhang, Qizhai Li, Peng Ding

  arXiv:2509.12587 PDF stat.ME
• Sep 03, 2025

  Covariate Adjustment Cannot Hurt: Treatment Effect Estimation under Interference with Low-Order Outcome Interactions

  Xinyi Wang, Shuangning Li

  arXiv:2509.03050 PDF stat.ME