Razieh Nabi - RankMe

37 papers A* 3A 6B 1Journal 25Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Coarsening Bias from Variable Discretization in Causal Functionals. CoRR Xiaxian Ou, Razieh Nabi
2026	J	`jnl`	Controllable Generative Sandbox for Causal Inference. CoRR Qi Zhang, Harsh Parikh, Ashley Naimi, Razieh Nabi, Christopher Kim, Timothy Lash
2026	J	`jnl`	MissNODAG: Differentiable Learning of Cyclic Causal Graphs from Incomplete Data. Trans. Mach. Learn. Res. Muralikrishnna G. Sethuraman, Razieh Nabi, Faramarz Fekri
2025	J	`jnl`	Bridging Prediction and Intervention Problems in Social Systems. CoRR 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, Michael Zanger-Tishler, Eli Ben-Michael, Solon Barocas, Avi Feller, Marissa Gerchick, Talia Gillis, Shion Guha, Daniel E. Ho, Lily Hu, Kosuke Imai, Sayash Kapoor, Joshua Loftus, Razieh Nabi, Arvind Narayanan, Ben Recht, Juan Carlos Perdomo, Matthew J. Salganik, Mark P. Sendak, Alexander Tolbert, Berk Ustun, Suresh Venkatasubramanian, Angelina Wang, Ashia Wilson
2025	J	`jnl`	Response to Discussions of "Causal and Counterfactual Views of Missing Data Models". CoRR Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser, James M. Robins
2024	J	`jnl`	Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door Criteria. CoRR Anna Guo, Razieh Nabi
2024	J	`jnl`	Fair Risk Minimization under Causal Path-Specific Effect Constraints. CoRR Razieh Nabi, David C. Benkeser
2024	J	`jnl`	MissNODAG: Differentiable Cyclic Causal Graph Learning from Incomplete Data. CoRR Muralikrishnna G. Sethuraman, Razieh Nabi, Faramarz Fekri
2024	J	`jnl`	Statistical learning for constrained functional parameters in infinite-dimensional models with applications in fair machine learning. CoRR Razieh Nabi, Nima S. Hejazi, Mark J. van der Laan, David C. Benkeser
2023	J	`jnl`	Ananke: A Python Package For Causal Inference Using Graphical Models. CoRR Jaron J. R. Lee, Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser
2023	—	`conf`	Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis. ISBI Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
2023	A	`conf`	On Testability and Goodness of Fit Tests in Missing Data Models. UAI Razieh Nabi, Rohit Bhattacharya
2023	A	`conf`	Sufficient identification conditions and semiparametric estimation under missing not at random mechanisms. UAI Anna Guo, Jiwei Zhao, Razieh Nabi
2022	J	`jnl`	Causal Inference in the Presence of Interference in Sponsored Search Advertising. Frontiers Big Data Razieh Nabi, Joel Pfeiffer, Denis Charles, Emre Kiciman
2022	J	`jnl`	Causal and counterfactual views of missing data models. CoRR Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser, James M. Robins
2022	B	`conf`	Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract). IEEE Big Data Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
2022	J	`jnl`	Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks. CoRR Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang
2022	J	`jnl`	On Testability and Goodness of Fit Tests in Missing Data Models. CoRR Razieh Nabi, Rohit Bhattacharya
2022	J	`jnl`	On Testability of the Front-Door Model via Verma Constraints. CoRR Rohit Bhattacharya, Razieh Nabi
2022	A	`conf`	On testability of the front-door model via Verma constraints. UAI Rohit Bhattacharya, Razieh Nabi
2022	—	`conf`	Optimal Training of Fair Predictive Models. CLeaR Razieh Nabi, Daniel Malinsky, Ilya Shpitser
2022	J	`jnl`	Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables. J. Mach. Learn. Res. Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser
2022	A	`conf`	Semiparametric causal sufficient dimension reduction of multidimensional treatments. UAI Razieh Nabi, Todd McNutt, Ilya Shpitser
2020	J	`jnl`	A Semiparametric Approach to Interpretable Machine Learning. CoRR Numair Sani, Jaron J. R. Lee, Razieh Nabi, Ilya Shpitser
2020	J	`jnl`	Causal Inference in the Presence of Interference in Sponsored Search Advertising. CoRR Razieh Nabi, Joel Pfeiffer, Murat Ali Bayir, Denis Charles, Emre Kiciman
2020	J	`jnl`	Full Law Identification In Graphical Models Of Missing Data: Completeness Results. CoRR Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser
2020	A*	`conf`	Full Law Identification in Graphical Models of Missing Data: Completeness Results. ICML Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser
2020	J	`jnl`	Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables. CoRR Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser
2019	A	`conf`	Identification In Missing Data Models Represented By Directed Acyclic Graphs. UAI Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins
2019	J	`jnl`	Identification In Missing Data Models Represented By Directed Acyclic Graphs. CoRR Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser, James M. Robins
2019	A*	`conf`	Learning Optimal Fair Policies. ICML Razieh Nabi, Daniel Malinsky, Ilya Shpitser
2019	J	`jnl`	Optimal Training of Fair Predictive Models. CoRR Razieh Nabi, Daniel Malinsky, Ilya Shpitser
2018	A	`conf`	Estimation of Personalized Effects Associated With Causal Pathways. UAI Razieh Nabi, Phyllis Kanki, Ilya Shpitser
2018	J	`jnl`	Estimation of Personalized Effects Associated With Causal Pathways. CoRR Razieh Nabi, Phyllis Kanki, Ilya Shpitser
2018	A*	`conf`	Fair Inference on Outcomes. AAAI Razieh Nabi, Ilya Shpitser
2018	J	`jnl`	Learning Optimal Fair Policies. CoRR Razieh Nabi, Daniel Malinsky, Ilya Shpitser
2017	J	`jnl`	coxphMIC: An R Package for Sparse Estimation of Cox Proportional Hazards Models via Approximated Information Criteria. R J. Razieh Nabi, Xiaogang Su