An End-to-End Pipeline for Causal ML with Continuous Treatments: An Application to Financial Decision Making
arXiv:2609.30396v1 Announce Type: cross Abstract: This paper presents an end-to-end causal machine learning (ML) pipeline designed for real-world applications with continuous treatments. The proposed framework consists of six sequential steps: dimensionality reduction, causal identification, positi…
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- 2026-09-28 04:00 · arXiv stat.ML
An End-to-End Pipeline for Causal ML with Continuous Treatments: An Application to Financial Decision Making