294 citations · 689 across the 21 of their papers we have counts for
6 papers · 1 filter
Partial Identifiability in Discrete Data With Measurement Error
Noam Finkelstein, Roy Adams, Suchi Saria +1
When data contains measurement errors, it is necessary to make assumptions relating the observed, erroneous data to the unobserved true phenomena of interest. These assumptions sho…
Identification Methods With Arbitrary Interventional Distributions as Inputs
Jaron J. R. Lee, Ilya Shpitser
Causal inference quantifies cause-effect relationships by estimating counterfactual parameters from data. This entails using \emph{identification theory} to establish a link betwee…
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…
Conditionally-additive-noise Models for Structure Learning
Daniel Chicharro, Stefano Panzeri, Ilya Shpitser
Constraint-based structure learning algorithms infer the causal structure of multivariate systems from observational data by determining an equivalent class of causal structures co…
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…
Parameter and Structure Learning in Nested Markov Models
Ilya Shpitser, Thomas S. Richardson, James M. Robins +1
The constraints arising from DAG models with latent variables can be naturally represented by means of acyclic directed mixed graphs (ADMGs). Such graphs contain directed and bidir…