Tag: double
-
Bayesian Double Descent
Bayesian Double Descent arXiv:2507.07338v1 Announce Type: new Abstract: Double descent is a phenomenon of over-parameterized statistical models. Our goal is to view double descent from a Bayesian perspective. Over-parameterized models such as deep neural networks have an interesting re-descending property in their risk characteristics. This is a recent phenomenon in machine learning and has been…
-
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments
Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments arXiv:2503.06156v1 Announce Type: new Abstract: Uncovering causal mediation effects is of significant value to practitioners seeking to isolate the direct treatment effect from the potential mediated effect. We propose a double machine learning (DML) algorithm for mediation analysis that supports continuous treatments. To estimate the…