Gaussian approximations in high dimensional estimation. - Vivek S. Borkar; Raaz Dwivedi; Neeraja Sahasrabudhe (Syst. Control. Lett., 2016)

Vaidya walk: A sampling algorithm based on the volumetric barrier. - Yuansi Chen; Raaz Dwivedi; Martin J. Wainwright; Bin Yu 001 (Allerton, 2017)

Theoretical guarantees for EM under misspecified Gaussian mixture models. - Raaz Dwivedi; Nhat Ho; Koulik Khamaru; Martin J. Wainwright; Michael I. Jordan (NeurIPS, 2018)

Fast MCMC Sampling Algorithms on Polytopes. - Yuansi Chen; Raaz Dwivedi; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2018)

Challenges with EM in application to weakly identifiable mixture models. - Raaz Dwivedi; Nhat Ho; Koulik Khamaru; Martin J. Wainwright; Michael I. Jordan; Bin Yu 001 (CoRR, 2019)

Log-concave sampling: Metropolis-Hastings algorithms are fast. - Raaz Dwivedi; Yuansi Chen; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2019)

Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. - Raaz Dwivedi; Nhat Ho; Koulik Khamaru; Martin J. Wainwright; Michael I. Jordan; Bin Yu 001 (AISTATS, 2020)

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)

Instability, Computational Efficiency and Statistical Accuracy. - Nhat Ho; Koulik Khamaru; Raaz Dwivedi; Martin J. Wainwright; Michael I. Jordan; Bin Yu 001 (CoRR, 2020)

Revisiting complexity and the bias-variance tradeoff. - Raaz Dwivedi; Chandan Singh; Bin Yu 001; Martin J. Wainwright (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)

Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients. - Yuansi Chen; Raaz Dwivedi; Martin J. Wainwright; Bin Yu 001 (J. Mach. Learn. Res., 2020)

Principled Statistical Approaches For Sampling and Inference in High Dimensions - Raaz Dwivedi (2021)

Generalized Kernel Thinning. - Raaz Dwivedi; Lester Mackey (ICLR, 2022)

Distribution Compression in Near-Linear Time. - Abhishek Shetty; Raaz Dwivedi; Lester Mackey (ICLR, 2022)

Counterfactual inference for sequential experimental design. - Raaz Dwivedi; Susan A. Murphy; Devavrat Shah (CoRR, 2022)

On counterfactual inference with unobserved confounding. - Abhin Shah; Raaz Dwivedi; Devavrat Shah; Gregory W. Wornell (CoRR, 2022)

Doubly robust nearest neighbors in factor models. - Raaz Dwivedi; Katherine Tian; Sabina Tomkins; Predrag V. Klasnja; Susan A. Murphy; Devavrat Shah (CoRR, 2022)

Compress Then Test: Powerful Kernel Testing in Near-linear Time. - Carles Domingo-Enrich; Raaz Dwivedi; Lester Mackey (AISTATS, 2023)

Revisiting minimum description length complexity in overparameterized models. - Raaz Dwivedi; Chandan Singh; Bin Yu 001; Martin J. Wainwright (J. Mach. Learn. Res., 2023)

Debiased Distribution Compression. - Lingxiao Li; Raaz Dwivedi; Lester Mackey (ICML, 2024)

Supervised Kernel Thinning. - Albert Gong; Kyuseong Choi; Raaz Dwivedi (NeurIPS, 2024)

Doubly Robust Inference in Causal Latent Factor Models. - Alberto Abadie; Anish Agarwal; Raaz Dwivedi; Abhin Shah (CoRR, 2024)

FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations. - Jane Dwivedi-Yu; Raaz Dwivedi; Timo Schick (CoRR, 2024)

Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space. - Jacob Feitelberg; Kyuseong Choi; Anish Agarwal; Raaz Dwivedi (CoRR, 2024)

Learning Counterfactual Distributions via Kernel Nearest Neighbors. - Kyuseong Choi; Jacob Feitelberg; Anish Agarwal; Raaz Dwivedi (CoRR, 2024)

Kernel Thinning. - Raaz Dwivedi; Lester Mackey (J. Mach. Learn. Res., 2024)

Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. - Susobhan Ghosh; Raphael Kim; Prasidh Chhabria; Raaz Dwivedi; Predrag Klasnja; Peng Liao; Kelly W. Zhang; Susan A. Murphy (Mach. Learn., 2024)

On adaptivity and minimax optimality of two-sided nearest neighbors. - Tathagata Sadhukhan; Manit Paul; Raaz Dwivedi (AISTATS, 2025)

Low-Rank Thinning. - Annabelle Michael Carrell; Albert Gong; Abhishek Shetty; Raaz Dwivedi; Lester Mackey (CoRR, 2025)

Adaptively-weighted Nearest Neighbors for Matrix Completion. - Tathagata Sadhukhan; Manit Paul; Raaz Dwivedi (CoRR, 2025)

N2: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion. - Caleb Chin; Aashish Khubchandani; Harshvardhan Maskara; Kyuseong Choi; Jacob Feitelberg; Albert Gong; Manit Paul; Tathagata Sadhukhan; Anish Agarwal; Raaz Dwivedi (CoRR, 2025)