43 citations · 143 across the 40 of their papers we have counts for
6 papers · 1 filter
MissNODAG: Differentiable Cyclic Causal Graph Learning from Incomplete Data
Muralikrishnna G. Sethuraman, Razieh Nabi, Faramarz Fekri
Causal discovery in real-world systems, such as biological networks, is often complicated by feedback loops and incomplete data. Standard algorithms, which assume acyclic structure…
Statistical learning for constrained functional parameters in infinite-dimensional models
Razieh Nabi, Nima S. Hejazi, Mark J. van der Laan +1
We develop a general framework for estimating function-valued parameters under equality or inequality constraints in infinite-dimensional statistical models. Such constrained learn…
Semiparametric Inference For Causal Effects In Graphical Models With Hidden Variables
Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser
Identification theory for causal effects in causal models associated with hidden variable directed acyclic graphs (DAGs) is well studied. However, the corresponding algorithms are…
Optimal Training of Fair Predictive Models
Razieh Nabi, Daniel Malinsky, Ilya Shpitser
Recently there has been sustained interest in modifying prediction algorithms to satisfy fairness constraints. These constraints are typically complex nonlinear functionals of the…
Identification In Missing Data Models Represented By Directed Acyclic Graphs
Rohit Bhattacharya, Razieh Nabi, Ilya Shpitser +1
Missing data is a pervasive problem in data analyses, resulting in datasets that contain censored realizations of a target distribution. Many approaches to inference on the target…
Fair Inference On Outcomes
Razieh Nabi, Ilya Shpitser
In this paper, we consider the problem of fair statistical inference involving outcome variables. Examples include classification and regression problems, and estimating treatment…