602 citations · 2.9k across the 103 of their papers we have counts for
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Discussion of `Multiscale Fisher's Independence Test for Multivariate Dependence'
Antonin Schrab, Wittawat Jitkrittum, Zoltán Szabó +2
We discuss how MultiFIT, the Multiscale Fisher's Independence Test for Multivariate Dependence proposed by Gorsky and Ma (2022), compares to existing linear-time kernel tests based…
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves
Rahul Singh, Liyuan Xu, Arthur Gretton
We propose simple nonparametric estimators for mediated and time-varying dose response curves based on kernel ridge regression. By embedding Pearl's mediation formula and Robins' g…
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments
Andreas Anastasiou, Alessandro Barp, François-Xavier Briol +11
Stein's method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin…
A kernel test for quasi-independence
Tamara Fernández, Wenkai Xu, Marc Ditzhaus +1
We consider settings in which the data of interest correspond to pairs of ordered times, e.g, the birth times of the first and second child, the times at which a new user creates a…
A kernel log-rank test of independence for right-censored data
Tamara Fernandez, Arthur Gretton, David Rindt +1
We introduce a general non-parametric independence test between right-censored survival times and covariates, which may be multivariate. Our test statistic has a dual interpretatio…
A maximum-mean-discrepancy goodness-of-fit test for censored data
Tamara Fernández, Arthur Gretton
We introduce a kernel-based goodness-of-fit test for censored data, where observations may be missing in random time intervals: a common occurrence in clinical trials and industria…