coxphMIC: An R Package for Sparse Estimation of Cox Proportional Hazards Models via Approximated Information Criteria. - Razieh Nabi; Xiaogang Su (R J., 2017)

Fair Inference on Outcomes. - Razieh Nabi; Ilya Shpitser (AAAI, 2018)

Estimation of Personalized Effects Associated With Causal Pathways. - Razieh Nabi; Phyllis Kanki; Ilya Shpitser (UAI, 2018)

Learning Optimal Fair Policies. - Razieh Nabi; Daniel Malinsky; Ilya Shpitser (ICML, 2019)

Identification In Missing Data Models Represented By Directed Acyclic Graphs. - Rohit Bhattacharya; Razieh Nabi; Ilya Shpitser; James M. Robins (UAI, 2019)

Full Law Identification in Graphical Models of Missing Data: Completeness Results. - Razieh Nabi; Rohit Bhattacharya; Ilya Shpitser (ICML, 2020)

A Semiparametric Approach to Interpretable Machine Learning. - Numair Sani; Jaron J. R. Lee; Razieh Nabi; Ilya Shpitser (CoRR, 2020)

Causal Inference in the Presence of Interference in Sponsored Search Advertising. - Razieh Nabi; Joel Pfeiffer; Murat Ali Bayir; Denis Charles; Emre Kiciman (CoRR, 2020)

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract). - Yue Yu 001; Xuan Kan; Hejie Cui; Ran Xu 002; Yujia Zheng 001; Xiangchen Song; Yanqiao Zhu 001; Kun Zhang 001; Razieh Nabi; Ying Guo 003; Chao Zhang 014; Carl Yang 001 (IEEE Big Data, 2022)

Optimal Training of Fair Predictive Models. - Razieh Nabi; Daniel Malinsky; Ilya Shpitser (CLeaR, 2022)

On testability of the front-door model via Verma constraints. - Rohit Bhattacharya; Razieh Nabi (UAI, 2022)

Semiparametric causal sufficient dimension reduction of multidimensional treatments. - Razieh Nabi; Todd McNutt; Ilya Shpitser (UAI, 2022)

Causal and counterfactual views of missing data models. - Razieh Nabi; Rohit Bhattacharya; Ilya Shpitser; James M. Robins (CoRR, 2022)

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks. - Yue Yu 001; Xuan Kan; Hejie Cui; Ran Xu 002; Yujia Zheng 001; Xiangchen Song; Yanqiao Zhu 001; Kun Zhang 001; Razieh Nabi; Ying Guo 003; Chao Zhang 014; Carl Yang 001 (CoRR, 2022)

Causal Inference in the Presence of Interference in Sponsored Search Advertising. - Razieh Nabi; Joel Pfeiffer; Denis Charles; Emre Kiciman (Frontiers Big Data, 2022)

Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables. - Rohit Bhattacharya; Razieh Nabi; Ilya Shpitser (J. Mach. Learn. Res., 2022)

Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis. - Yue Yu 001; Xuan Kan; Hejie Cui; Ran Xu 002; Yujia Zheng 001; Xiangchen Song; Yanqiao Zhu 001; Kun Zhang 001; Razieh Nabi; Ying Guo 003; Chao Zhang 014; Carl Yang 001 (ISBI, 2023)

Sufficient identification conditions and semiparametric estimation under missing not at random mechanisms. - Anna Guo; Jiwei Zhao; Razieh Nabi (UAI, 2023)

On Testability and Goodness of Fit Tests in Missing Data Models. - Razieh Nabi; Rohit Bhattacharya (UAI, 2023)

Ananke: A Python Package For Causal Inference Using Graphical Models. - Jaron J. R. Lee; Rohit Bhattacharya; Razieh Nabi; Ilya Shpitser (CoRR, 2023)

Statistical learning for constrained functional parameters in infinite-dimensional models with applications in fair machine learning. - Razieh Nabi; Nima S. Hejazi; Mark J. van der Laan; David C. Benkeser (CoRR, 2024)

Fair Risk Minimization under Causal Path-Specific Effect Constraints. - Razieh Nabi; David C. Benkeser (CoRR, 2024)

Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door Criteria. - Anna Guo; Razieh Nabi (CoRR, 2024)

MissNODAG: Differentiable Cyclic Causal Graph Learning from Incomplete Data. - Muralikrishnna G. Sethuraman; Razieh Nabi; Faramarz Fekri (CoRR, 2024)

Bridging Prediction and Intervention Problems in Social Systems. - Lydia T. Liu; Inioluwa Deborah Raji; Angela Zhou; Luke Guerdan; Jessica Hullman; Daniel Malinsky; Bryan Wilder; Simone Zhang; Hammaad Adam; Amanda Coston; Benjamin Laufer; Ezinne Nwankwo; et al. (CoRR, 2025)