Razieh Nabi

According to our database1, Razieh Nabi authored at least 24 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
MissNODAG: Differentiable Cyclic Causal Graph Learning from Incomplete Data.
CoRR, 2024

Average Causal Effect Estimation in DAGs with Hidden Variables: Extensions of Back-Door and Front-Door Criteria.
CoRR, 2024

Fair Risk Minimization under Causal Path-Specific Effect Constraints.
CoRR, 2024

Statistical learning for constrained functional parameters in infinite-dimensional models with applications in fair machine learning.
CoRR, 2024

2023
Ananke: A Python Package For Causal Inference Using Graphical Models.
CoRR, 2023

On Testability and Goodness of Fit Tests in Missing Data Models.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Sufficient identification conditions and semiparametric estimation under missing not at random mechanisms.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

2022
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables.
J. Mach. Learn. Res., 2022

Causal Inference in the Presence of Interference in Sponsored Search Advertising.
Frontiers Big Data, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks.
CoRR, 2022

Causal and counterfactual views of missing data models.
CoRR, 2022

Semiparametric causal sufficient dimension reduction of multidimensional treatments.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

On testability of the front-door model via Verma constraints.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Optimal Training of Fair Predictive Models.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022

2020
Causal Inference in the Presence of Interference in Sponsored Search Advertising.
CoRR, 2020

A Semiparametric Approach to Interpretable Machine Learning.
CoRR, 2020

Full Law Identification in Graphical Models of Missing Data: Completeness Results.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Identification In Missing Data Models Represented By Directed Acyclic Graphs.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Learning Optimal Fair Policies.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Estimation of Personalized Effects Associated With Causal Pathways.
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Fair Inference on Outcomes.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
coxphMIC: An R Package for Sparse Estimation of Cox Proportional Hazards Models via Approximated Information Criteria.
R J., 2017


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