Instrumental Variable Methods for Sequential Experiment Design
MCML Authors
Elisabeth Ailer
Abstract
Elisabeth Ailer
Abstract
This thesis develops instrumental variable (IV) techniques for sequential experimental design to quantify causal relationships in high-dimensional systems with hidden confounders. Motivated by challenges in biological datasets—such as high dimensionality, hidden confounding, nonlinear effects, and limited resources—we address these issues by extending IV methods to underspecified linear and nonlinear settings, refining bounds for causal effects, and optimizing experiment selection.
BibTeXKey: Ail25