Search Results for author:
Found 3 papers, 0 papers with code
Generalization of LiNGAM that allows confounding
LiNGAM determines the variable order from cause to effect using additive noise models, but it faces challenges with confounding.
Functional Linear Non-Gaussian Acyclic Model for Causal Discovery
To expand this concept, we extend the notion of variables to encompass vectors and even functions, leading to the Functional Linear Non-Gaussian Acyclic Model (Func-LiNGAM).
Dropout Drops Double Descent
Our paper posits that the optimal test error, in terms of the dropout rate, shows a monotonic decrease in linear regression with increasing sample size.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
