activity
20092024
most citedGeometry of the faithfulness assumption in causal inference

161 citations · 243 across the 21 of their papers we have counts for

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8 papers · 1 filter

stat.ME2021★ 1 cited

Matching a Desired Causal State via Shift Interventions

Jiaqi Zhang, Chandler Squires, Caroline Uhler

Transforming a causal system from a given initial state to a desired target state is an important task permeating multiple fields including control theory, biology, and materials s…

stat.ME2020★ 1 cited

Efficient Permutation Discovery in Causal DAGs

Chandler Squires, Joshua Amaniampong, Caroline Uhler

The problem of learning a directed acyclic graph (DAG) up to Markov equivalence is equivalent to the problem of finding a permutation of the variables that induces the sparsest gra…

stat.ME2019

Permutation-Based Causal Structure Learning with Unknown Intervention Targets

Chandler Squires, Yuhao Wang, Caroline Uhler

We consider the problem of estimating causal DAG models from a mix of observational and interventional data, when the intervention targets are partially or completely unknown. This…

stat.ME2019★ 3 cited

Anchored Causal Inference in the Presence of Measurement Error

Basil Saeed, Anastasiya Belyaeva, Yuhao Wang +1

We consider the problem of learning a causal graph in the presence of measurement error. This setting is for example common in genomics, where gene expression is corrupted through…

stat.ME2019

Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters

Yuhao Wang, Uma Roy, Caroline Uhler

We consider the problem of estimating an undirected Gaussian graphical model when the underlying distribution is multivariate totally positive of order 2 (MTP2), a strong form of p…

stat.ME2019★ 10 cited

ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery

Raj Agrawal, Chandler Squires, Karren Yang +2

Determining the causal structure of a set of variables is critical for both scientific inquiry and decision-making. However, this is often challenging in practice due to limited in…