Introduces OR-learners that can strictly improve estimation error of standard Neyman-orthogonal learners under the low-dimensional manifold hypothesis, while showing that balancing constraints require additional inductive bias.
K¨ unzel, Jasjeet S
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Orthogonal Representation Learning for Estimating Causal Quantities
Introduces OR-learners that can strictly improve estimation error of standard Neyman-orthogonal learners under the low-dimensional manifold hypothesis, while showing that balancing constraints require additional inductive bias.