  In this paper, we introduce and prove asymptotic normality for a new
nonparametric estimator of continuous treatment effects. Specifically, we
estimate the average dose-response function - the expected value of an outcome
of interest at a particular level of the treatment level. We utilize tools from
both the double debiased machine learning (DML) and the automatic double
machine learning (ADML) literatures to construct our estimator. Our estimator
utilizes a novel debiasing method that leads to nice theoretical stability and
balancing properties. In simulations our estimator performs well compared to
current methods.
