Energy optimization for distributions on the sphere and improvement to the Welch bounds. - Yan Shuo Tan (CoRR, 2016)

Phase Retrieval via Randomized Kaczmarz: Theoretical Guarantees. - Yan Shuo Tan; Roman Vershynin (CoRR, 2017)

Sparse Phase Retrieval via Sparse PCA Despite Model Misspecification: A Simplified and Extended Analysis. - Yan Shuo Tan (CoRR, 2017)

Polynomial Time and Sample Complexity for Non-Gaussian Component Analysis: Spectral Methods. - Yan Shuo Tan; Roman Vershynin (COLT, 2018)

Curating a COVID-19 data repository and forecasting county-level death counts in the United States. - Nick Altieri 001; Rebecca L. Barter; James Duncan 002; Raaz Dwivedi; Karl Kumbier; Xiao Li; Robert Netzorg; Briton Park; Chandan Singh; Yan Shuo Tan; Tiffany M. Tang; Yu Wang 075; et al. (CoRR, 2020)

Stable discovery of interpretable subgroups via calibration in causal studies. - Raaz Dwivedi; Yan Shuo Tan; Briton Park; Mian Wei; Kevin Horgan; David Madigan; Bin Yu 001 (CoRR, 2020)

imodels: a python package for fitting interpretable models. - Chandan Singh; Keyan Nasseri; Yan Shuo Tan; Tiffany M. Tang; Bin Yu 001 (J. Open Source Softw., 2021)

A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds. - Yan Shuo Tan; Abhineet Agarwal; Bin Yu 001 (AISTATS, 2022)

Hierarchical Shrinkage: Improving the accuracy and interpretability of tree-based models. - Abhineet Agarwal; Yan Shuo Tan; Omer Ronen; Chandan Singh; Bin Yu 001 (ICML, 2022)

Fast Interpretable Greedy-Tree Sums (FIGS). - Yan Shuo Tan; Chandan Singh; Keyan Nasseri; Abhineet Agarwal; Bin Yu 001 (CoRR, 2022)

Hierarchical Shrinkage: improving the accuracy and interpretability of tree-based methods. - Abhineet Agarwal; Yan Shuo Tan; Omer Ronen; Chandan Singh; Bin Yu 001 (CoRR, 2022)

A Mixing Time Lower Bound for a Simplified Version of BART. - Omer Ronen; Theo Saarinen; Yan Shuo Tan; James Duncan 002; Bin Yu 001 (CoRR, 2022)

MDI+: A Flexible Random Forest-Based Feature Importance Framework. - Abhineet Agarwal; Ana M. Kenney; Yan Shuo Tan; Tiffany M. Tang; Bin Yu 001 (CoRR, 2023)

Error Reduction from Stacked Regressions. - Xin Chen; Jason M. Klusowski; Yan Shuo Tan (CoRR, 2023)

Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval. - Yan Shuo Tan; Roman Vershynin (J. Mach. Learn. Res., 2023)

The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time Analysis. - Yan Shuo Tan; Omer Ronen; Theo Saarinen; Bin Yu 001 (CoRR, 2024)

Bayesian Concept Bottleneck Models with LLM Priors. - Jean Feng; Avni Kothari; Luke Zier; Chandan Singh; Yan Shuo Tan (CoRR, 2024)

Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators. - Yan Shuo Tan; Jason M. Klusowski; Krishnakumar Balasubramanian 002 (CoRR, 2024)

TabPFN: One Model to Rule Them All? - Qiong Zhang; Yan Shuo Tan; Qinglong Tian; Pengfei Li (CoRR, 2025)

Revisiting Randomization in Greedy Model Search. - Xin Chen; Jason M. Klusowski; Yan Shuo Tan; Chang Yu (CoRR, 2025)

See-in-Pairs: Reference Image-Guided Comparative Vision-Language Models for Medical Diagnosis. - Ruinan Jin; Gexin Huang; Xinwei Shen; Qiong Zhang; Yan Shuo Tan; Xiaoxiao Li (CoRR, 2025)