Papers

A collection of research papers I've read and found insightful.

  1. Data Fusion for High-Resolution Estimation
    Amy Guan, Roshni Sahoo, Joshua Salomon, Stefan Wager, and Marissa Reitsma
    Jun 2026
  2. Catastrophe Insurance: An Adaptive Robust Optimization Approach
    Dimitris Bertsimas, and Cynthia Zeng
    May 2024
  3. Convexification of multi-period quadratic programs with indicators
    Jisun Lee, Andrés Gómez, and Alper Atamtürk
    arXiv preprint arXiv:2412.17178, May 2024
  4. Score-Based Generative Modeling through Stochastic Differential Equations
    Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole
    In International Conference on Learning Representations (ICLR), May 2021
  5. Denoising Diffusion Probabilistic Models
    Jonathan Ho, Ajay Jain, and Pieter Abbeel
    In Advances in Neural Information Processing Systems, May 2020
  6. Building representative matched samples with multi-valued treatments in large observational studies
    Magdalena Bennett, Juan Pablo Vielma, and José R Zubizarreta
    Journal of Computational and Graphical Statistics, May 2020
  7. Sensitivity Analysis for Inverse Probability Weighting Estimators via the Percentile Bootstrap
    Qingyuan Zhao, Dylan S. Small, and Bhaswar B. Bhattacharya
    Journal of the Royal Statistical Society Series B: Statistical Methodology, Sep 2019
  8. Robust classification
    Dimitris Bertsimas, Jack Dunn, Colin Pawlowski, and Ying Daisy Zhuo
    INFORMS Journal on Optimization, Sep 2019
  9. Best Subset Selection via a Modern Optimization Lens
    Dimitris Bertsimas, Angela King, and Rahul Mazumder
    The Annals of Statistics, Apr 2016
  10. Performance Guarantees for Individualized Treatment Rules
    Min Qian, and Susan A. Murphy
    The Annals of Statistics, Apr 2011
  11. A Distributional Approach for Causal Inference Using Propensity Scores
    Zhiqiang Tan
    Journal of the American Statistical Association, Dec 2006