From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding
One of the central goals of causal machine learning is the accurate estimation of
heterogeneous treatment effects from observational data. In recent years, meta-learning has …
heterogeneous treatment effects from observational data. In recent years, meta-learning has …
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
V Melnychuk, S Feuerriegel… - arXiv preprint arXiv …, 2024 - arxiv.org
Estimating causal quantities from observational data is crucial for understanding the safety
and effectiveness of medical treatments. However, to make reliable inferences, medical …
and effectiveness of medical treatments. However, to make reliable inferences, medical …
Conformal Prediction for Dose-Response Models with Continuous Treatments
Understanding the dose-response relation between a continuous treatment and the
outcome for an individual can greatly drive decision-making, particularly in areas like …
outcome for an individual can greatly drive decision-making, particularly in areas like …
Conformal Predictive Systems Under Covariate Shift
Conformal Predictive Systems (CPS) offer a versatile framework for constructing predictive
distributions, allowing for calibrated inference and informative decision-making. However …
distributions, allowing for calibrated inference and informative decision-making. However …