Maya Ramachandran, Rajarshi Mukherjee, and Giovanni Parmigiani. Submitted. “Cross-Cluster Weighted Forests”. Arxiv

Nabarun Deb, Rajarshi Mukherjee, Sumit Mukherjee, and Ming Yuan. Submitted. “Detecting Structured Signals in Ising Models ”. Arxiv

Alexander Levis, Rajarshi Mukherjee, Rui Wang, and Sebastien Haneuse. Submitted. “Double sampling and semiparametric methods for informatively missing data”. Arxiv

Jue Hou, Rajarshi Mukherjee, and Tianxi Cai. Submitted. “Efficient and Robust Semi-supervised Estimation of ATE with Partially Annotated Treatment and Response”. Arxiv

Maya Ramachandran and Rajarshi Mukherjee. Submitted. “ On Ensembling vs Merging: Least Squares and Random Forests under Covariate Shift”. Arxiv

Nilanjana Laha, Aaron Sonabend, Rajarshi Mukherjee, and Tianxi Cai. Submitted. “Finding the Optimal Dynamic Treatment Regime Using Fisher Consistent Surrogate Loss ”. Arxiv

Sohom Bhattacharya, Rajarshi Mukherjee, and Rounak Dey. Submitted. “PC Adjusted Testing for Low Dimensional Parameters”. Arxiv

Sohom Bhattacharya, Rajarshi Mukherjee, and Gourab Ray. Submitted. “Sharp Signal Detection Under Ferromagnetic Ising Models”. Arxiv

Julien Chhor, Rajarshi Mukherjee, and Subhabrata Sen. Submitted. “Sparse Signal Detection in Heteroscedastic Gaussian Sequence Models: Sharp Minimax Rates”. Arxiv

Rajarshi Mukherjee and Subhabrata Sen. Submitted. “On Minimax Exponents of Sparse Testing”. Arxiv

Kuanhao Jiang, Rajarshi Mukherjee, Subhabrata Sen, and Pragya Sur. Submitted. “A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance, and Beyond”. Arxiv

Rajarshi Mukherjee, Whitney Newey, and James Robins. Submitted. “Semiparametric Efficient Empirical Higher Order Influence Function Estimators”. Arxiv

Aaron Sonabend, Nilanjana Laha, Ashwin N. Ananthakrishnan, Tianxi Cai, and Rajarshi Mukherjee. Submitted. “Semi-Supervised Off Policy Reinforcement Learning”. Arxiv

Bhaswar B. Bhattacharya and Rajarshi Mukherjee. Submitted. “Sparse Uniformity Testing”. Arxiv

Nilanjana Laha, Nathan Huey, Brent Coull, and Rajarshi Mukherjee. Submitted. “On Statistical Inference with High Dimensional Sparse CCA”. Arxiv

Yu-Jyun Huang, Rajarshi Mukherjee, and Chuhsing Kate Hsiao. 2022. “Probabilistic Edge Inference of Gene Networks with Bayesian Markov Random Field Modeling.” Frontiers in Genetics. bioRxiv

Nilanjana Laha and Rajarshi Mukherjee. 2022. “On Support Recovery With Sparse CCA: Information Theoretic and Computational Limits.” IEEE Transactions of Information Theory. Arxiv

Wenying Deng, Beau Cocker, Rajarshi Mukherjee, Jeremiah Zhe Liu, and Brent Coull. 2022. “Towards a Unified Framework for Uncertainty-aware Nonlinear Variable Selection with Theoretical Guarantees.” NeurIPS. Arxiv

Weeberb J. Requia, Heresh Amini, Rajarshi Mukherjee, Diane R. Gold, and Joel D. Schwartz. 2021. “Health impacts of wildfire-related air pollution in Brazil: A nationwide of more than 2 million hospital admissions between 2008 and 2018.” Nature Communications.

Chi-Hsuan Ho, Yu-Jyun Huang, Ying-Ju Lai, Rajarshi Mukherjee, and Chuhsing Kate Hsiao. 2021. “The misuse of distributional assumptions in functional class scoring gene-set and pathway analysis.” G3: Genes Genomes Genetics.