10 citations · 17 across the 11 of their papers we have counts for
4 papers · 1 filter
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
Philippe Brouillard, Chandler Squires, Jonas Wahl +4
Causal discovery aims to automatically uncover causal relationships from data, a capability with significant potential across many scientific disciplines. However, its real-world a…
Probably approximately correct high-dimensional causal effect estimation given a valid adjustment set
Davin Choo, Chandler Squires, Arnab Bhattacharyya +1
Accurate estimates of causal effects play a key role in decision-making across applications such as healthcare, economics, and operations. In the absence of randomized experiments,…
Synthetic Potential Outcomes and Causal Mixture Identifiability
Bijan Mazaheri, Chandler Squires, Caroline Uhler
Heterogeneous data from multiple populations, sub-groups, or sources is often represented as a ``mixture model'' with a single latent class influencing all of the observed covariat…
Causal Imputation for Counterfactual SCMs: Bridging Graphs and Latent Factor Models
Alvaro Ribot, Chandler Squires, Caroline Uhler
We consider the task of causal imputation, where we aim to predict the outcomes of some set of actions across a wide range of possible contexts. As a running example, we consider p…