On Doubly Robust Inference for Double Machine Learning in ...

[2107.06124] On doubly robust inference for double machine learning

Focusing on partially linear regression models, we show that a specific implementation of the machine learning techniques can yield exposure ...

(2017) differs from. 2. Page 3. Doubly Robust Inference for Double Machine Learning the usual one of n−1 times the sample variance of the efficient influence ...

On doubly robust inference for double machine learning - arXiv

Such ideas underpin developments in targeted minimum loss estimation (TMLE) (van der Laan and Rose, 2011), and double machine learning (DML). ( ...

Is double machine learning doubly robust? If so, how?

Yes, but only because double machine learning uses a doubly robust estimator underneath the hood. There is nothing about the cross-fitting ...

(PDF) On doubly robust inference for double machine learning

Unfortunately, exposure effect estimators that rely on machine learning predictions are generally subject to so-called plug-in bias, which can ...

Journal of Machine Learning Research on X: "'On Doubly Robust ...

'On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression', by Oliver Dukes, Stijn Vansteelandt, David Whitney.

Doubly Robust Machine Learning papers/books - Reddit

... double ML” or doubly robust ML. These are methods to ... Doubly Robust Machine Learning papers/books ... inference and machine learning. You might ...

Double debiased machine learning nonparametric inference with ...

Using doubly robust influence function and cross-fitting, we give tractable primitive conditions under which the nuisance estimators do not affect the first- ...

Good reading on when "doubly robust" is worth the effort?

... robust to model misspecification. And it ... machine learning algorithms as part of your estimation procedure. ... double robustness is ...

Doubly Robust Learning — econml 0.15.1 documentation

Doubly Robust Learning, similar to Double Machine Learning, is a method for ... inference (confidence interval construction) for measuring the uncertainty of the ...

6.5 - Doubly Robust Methods, Matching, Double Machine ... - YouTube

In this part of the Introduction to Causal Inference course, we sketch out a few other methods for causal effect estimation: doubly robust ...

STA 640 — Causal Inference Chapter 3.5. Doubly Robust Estimation

semiparametric ones via splines, power series, machine learning ... Doubly robust estimation in missing data and causal inference ... double-robust estimators when ...

Doubly robust learning for causal inference - Dan MacKinlay

To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of ...

Doubly Robust Inference in Causal Latent Factor Models

Doubly Robust Inference in Causal Latent Factor Models ... Double/debiased machine learning for treatment and structural parame- ters.

Double Debiased Machine Learning Nonparametric Inference with ...

We propose a doubly robust inference method for causal effects of continuous treatment variables, under unconfoundedness and with nonparametric or ...

Selective machine learning of doubly robust functionals | Biometrika

Valid inference may then be obtained about the functional of interest provided that nuisance parameters can be estimated at sufficiently fast ...

Estimating causal effects under sparsity using the econml package

In this post, I'll introduce the econml python package and use it to compare double machine learning and doubly robust learning.

Minimax Kernel Machine Learning for a Class of Doubly Robust ...

Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference ... Then we demonstrate that the double ...

Doubly Robust Estimation — Causal Inference for the Brave and True

Don't Put All your Eggs in One Basket#. We've learned how to use linear regression and propensity score weighting to estimate ...

Double/debiased machine learning for logistic partially linear model

Our double machine learning (DML) estimator for β 0 is rated doubly robust in the same sense as Chernozhukov, Chetverikov, et al. (2018), i.e., ...