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Omniscience in Adversarial Causal Inference: Implications for Balancing Estimators of Average Treatment Effects
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Methods for Improving Doubly Robust Estimators of Treatment Effects for Observational Studies and Randomized Trials
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Advances in Causal Inference to Support Vaccine Development and Evaluation
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Semiparametric Efficient Designs with Staggered Rollouts
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Methods for Improving the Interpretability and Evaluation of Machine Learning Models and Decision Making Systems
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Causal Inference in Multilayered Networks
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Courts, Constraints, and Public Opinion in Europe
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Stability of Inference Derived from Machine Learning-based Doubly Robust Estimators of Treatment Effects
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Estimation of Potential Outcomes when Treatment Assignment and Discontinuation Compete in Observational Data
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Quantifying the Impact of Local SUTVA Violations in Spatiotemporal Causal Models
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