Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Covariate-Balancing-Aware Interpretable Deep Learning models for
  Treatment Effect Estimation   Estimating treatment effects is of great importance for many biomedical
applications with observational data. Particularly, interpretability of the
treatment effects is preferable for many biomedical researchers. In this paper,
we first give a theoretical analysis and propose an upper bound for the bias of
average treatment effect estimation under the strong ignorability assumption.
The proposed upper bound consists of two parts: training error for factual
outcomes, and the distance between treated and control distributions. We use
the Weighted Energy Distance (WED) to measure the distance between two
distributions. Motivated by the theoretical analysis, we implement this upper
bound as an objective function being minimized by leveraging a novel additive
neural network architecture, which combines the expressivity of deep neural
network, the interpretability of generalized additive model, the sufficiency of
the balancing score for estimation adjustment, and covariate balancing
properties of treated and control distributions, for estimating average
treatment effects from observational data. Furthermore, we impose a so-called
weighted regularization procedure based on non-parametric theory, to obtain
some desirable asymptotic properties. The proposed method is illustrated by
re-examining the benchmark datasets for causal inference, and it outperforms
the state-of-art.

27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
32
The categories of this paper are: atom-ph