Conformal prediction and other randomized model-free inference technique...
Early stopping based on hold-out data is a popular regularization techni...
A flexible method is developed to construct a confidence interval for th...
The estimation of coverage probabilities, and in particular of the missi...
This paper develops novel conformal methods to test whether a new observ...
Double machine learning is a statistical method for leveraging complex
b...
Model-X knockoffs and the conditional randomization test are methods tha...
Deep neural networks are powerful tools to detect hidden patterns in dat...
A flexible conformal inference method is developed to construct confiden...
This paper presents and compares alternative transfer learning methods t...
This paper develops a method based on model-X knockoffs to find conditio...
This paper develops a conformal method to compute prediction intervals f...
This paper studies the construction of p-values for nonparametric outlie...
Interpretability is important for many applications of machine learning ...
Conformal inference, cross-validation+, and the jackknife+ are hold-out
...
We introduce a method to rigorously draw causal inferences—inferences
im...
We compare two recently proposed methods that combine ideas from conform...
In this paper we deepen and enlarge the reflection on the possible advan...
This paper introduces a machine for sampling approximate model-X knockof...