Picture for Wenkai Xu

Wenkai Xu

Split Conformal Prediction under Data Contamination

Add code
Jul 10, 2024
Viaarxiv icon

SteinGen: Generating Fidelitous and Diverse Graph Samples

Add code
Apr 04, 2024
Viaarxiv icon

Nonlinear Causal Discovery via Kernel Anchor Regression

Add code
Oct 30, 2022
Viaarxiv icon

On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics

Add code
Oct 11, 2022
Figure 1 for On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics
Figure 2 for On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics
Figure 3 for On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics
Figure 4 for On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics
Viaarxiv icon

A Kernelised Stein Statistic for Assessing Implicit Generative Models

Add code
May 31, 2022
Figure 1 for A Kernelised Stein Statistic for Assessing Implicit Generative Models
Figure 2 for A Kernelised Stein Statistic for Assessing Implicit Generative Models
Figure 3 for A Kernelised Stein Statistic for Assessing Implicit Generative Models
Figure 4 for A Kernelised Stein Statistic for Assessing Implicit Generative Models
Viaarxiv icon

AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators

Add code
Mar 07, 2022
Figure 1 for AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators
Figure 2 for AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators
Figure 3 for AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators
Figure 4 for AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators
Viaarxiv icon

Generalised Kernel Stein Discrepancy(GKSD): A Unifying Approach for Non-parametric Goodness-of-fit Testing

Add code
Jun 23, 2021
Figure 1 for Generalised Kernel Stein Discrepancy(GKSD): A Unifying Approach for Non-parametric Goodness-of-fit Testing
Figure 2 for Generalised Kernel Stein Discrepancy(GKSD): A Unifying Approach for Non-parametric Goodness-of-fit Testing
Figure 3 for Generalised Kernel Stein Discrepancy(GKSD): A Unifying Approach for Non-parametric Goodness-of-fit Testing
Figure 4 for Generalised Kernel Stein Discrepancy(GKSD): A Unifying Approach for Non-parametric Goodness-of-fit Testing
Viaarxiv icon

Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data

Add code
Jun 14, 2021
Figure 1 for Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
Figure 2 for Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
Figure 3 for Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
Figure 4 for Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data
Viaarxiv icon

A Stein Goodness of fit Test for Exponential Random Graph Models

Add code
Feb 28, 2021
Figure 1 for A Stein Goodness of fit Test for Exponential Random Graph Models
Figure 2 for A Stein Goodness of fit Test for Exponential Random Graph Models
Figure 3 for A Stein Goodness of fit Test for Exponential Random Graph Models
Figure 4 for A Stein Goodness of fit Test for Exponential Random Graph Models
Viaarxiv icon

A kernel test for quasi-independence

Add code
Nov 17, 2020
Figure 1 for A kernel test for quasi-independence
Figure 2 for A kernel test for quasi-independence
Figure 3 for A kernel test for quasi-independence
Figure 4 for A kernel test for quasi-independence
Viaarxiv icon