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Nonlinear Sufficient Dimension Reduction for Causal Inference with Continuous Treatments
Causal inference with continuous treatments requires estimating nuisance functions to adjust for the potentially high-dimensional confounder, but nonparametric estimation of these functions is severely hampered by the curse of dimensionality. To address this challenge, we propose a nonlinear suffici
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