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20192026
most citedKernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data

6 citations · 15 across the 11 of their papers we have counts for

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8 papers · 1 filter

stat.ML2026

A Kernel Nonconformity Score for Multivariate Conformal Prediction

Louis Meyer, Wenkai Xu

Multivariate conformal prediction requires nonconformity scores that compress residual vectors into scalars while preserving certain implicit geometric structure of the residual di…

stat.ML2024

Split Conformal Prediction under Data Contamination

Jase Clarkson, Wenkai Xu, Mihai Cucuringu +2

Conformal prediction is a non-parametric technique for constructing prediction intervals or sets from arbitrary predictive models under the assumption that the data is exchangeable…

stat.ML2024

SteinGen: Generating Fidelitous and Diverse Graph Samples

Gesine Reinert, Wenkai Xu

Generating graphs that preserve characteristic structures while promoting sample diversity can be challenging, especially when the number of graph observations is small. Here, we t…

stat.ML2022

Nonlinear Causal Discovery via Kernel Anchor Regression

Wenqi Shi, Wenkai Xu

Learning causal relationships is a fundamental problem in science. Anchor regression has been developed to address this problem for a large class of causal graphical models, though…

stat.ML2022

On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics

Moritz Weckbecker, Wenkai Xu, Gesine Reinert

Score-based kernelised Stein discrepancy (KSD) tests have emerged as a powerful tool for the goodness of fit tests, especially in high dimensions; however, the test performance may…

stat.ML20206 cited

Kernelized Stein Discrepancy Tests of Goodness-of-fit for Time-to-Event Data

Tamara Fernandez, Nicolas Rivera, Wenkai Xu +1

Survival Analysis and Reliability Theory are concerned with the analysis of time-to-event data, in which observations correspond to waiting times until an event of interest such as…