Domain Counterfactuals for Trustworthy ML via Sparse Interventions | David I. Inouye
Halıcıoğlu Data Science Institute (HDSI), Room 404 3234 Matthews Ln, La Jolla, CA, United StatesTalk Abstract: Although incorporating causal concepts into deep learning shows promise for increasing explainability, fairness, and robustness, existing methods require unrealistic assumptions and aim to recover the full latent causal model. This talk proposes an alternative: domain counterfactuals. Domain counterfactuals ask a more concrete question: "What would a sample look like if it had been […]