Dennis Frauen

LLM development is flying blind by ignoring causal inference, leaving models vulnerable to confounding and distribution shifts throughout pretraining, alignment, and evaluation.

Naive neural operator estimates of solution functional quantities can be significantly biased, but this paper provides a surprisingly simple debiasing technique to fix it.

Unstable estimates in long-term treatment effect prediction? These orthogonal learners use custom overlap weights to improve robustness in low-overlap settings common in long-term outcomes.

Turn your favorite causal machine learning estimator into a fully Bayesian one with calibrated uncertainty, without needing to specify complex likelihood models.