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MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting
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MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting

Felix Biggs
Antonin Schrab
Arthur Gretton
ArXiv (abs)PDFHTML

Papers citing "MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting"

8 / 8 papers shown
Title
Kernel Quantile Embeddings and Associated Probability Metrics
Kernel Quantile Embeddings and Associated Probability Metrics
Masha Naslidnyk
Siu Lun Chau
F. Briol
Krikamol Muandet
76
0
0
26 May 2025
A Unified View of Optimal Kernel Hypothesis Testing
Antonin Schrab
87
3
0
10 Mar 2025
A Practical Introduction to Kernel Discrepancies: MMD, HSIC & KSD
Antonin Schrab
77
1
0
04 Mar 2025
Particle Semi-Implicit Variational Inference
Particle Semi-Implicit Variational Inference
Jen Ning Lim
A. M. Johansen
124
7
0
30 Jun 2024
Robust Kernel Hypothesis Testing under Data Corruption
Robust Kernel Hypothesis Testing under Data Corruption
Antonin Schrab
Ilmun Kim
107
4
0
30 May 2024
To smooth a cloud or to pin it down: Guarantees and Insights on Score Matching in Denoising Diffusion Models
To smooth a cloud or to pin it down: Guarantees and Insights on Score Matching in Denoising Diffusion Models
Francisco Vargas
Teodora Reu
A. Kerekes
Michael M Bronstein
DiffM
105
1
0
16 May 2023
Compress Then Test: Powerful Kernel Testing in Near-linear Time
Compress Then Test: Powerful Kernel Testing in Near-linear Time
Carles Domingo-Enrich
Raaz Dwivedi
Lester W. Mackey
151
10
0
14 Jan 2023
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
358
4,115
0
17 Jun 2020