4 citations · 5 across the 13 of their papers we have counts for
5 papers · 1 filter
Learning Mixtures of Unknown Causal Interventions
Abhinav Kumar, Kirankumar Shiragur, Caroline Uhler
The ability to conduct interventions plays a pivotal role in learning causal relationships among variables, thus facilitating applications across diverse scientific disciplines suc…
Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
Many questions in science center around the fundamental problem of understanding causal relationships. However, most constraint-based causal discovery algorithms, including the wel…
Season combinatorial intervention predictions with Salt & Peper
Thomas Gaudelet, Alice Del Vecchio, Eli M Carrami +4
Interventions play a pivotal role in the study of complex biological systems. In drug discovery, genetic interventions (such as CRISPR base editing) have become central to both ide…
Membership Testing in Markov Equivalence Classes via Independence Query Oracles
Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler
Understanding causal relationships between variables is a fundamental problem with broad impact in numerous scientific fields. While extensive research has been dedicated to learni…
Causal Discovery under Off-Target Interventions
Davin Choo, Kirankumar Shiragur, Caroline Uhler
Causal graph discovery is a significant problem with applications across various disciplines. However, with observational data alone, the underlying causal graph can only be recove…