ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1708.08157
  4. Cited By
Characteristic and Universal Tensor Product Kernels

Characteristic and Universal Tensor Product Kernels

28 August 2017
Z. Szabó
Bharath K. Sriperumbudur
ArXivPDFHTML

Papers citing "Characteristic and Universal Tensor Product Kernels"

18 / 18 papers shown
Title
Learning Deep Kernels for Non-Parametric Independence Testing
Learning Deep Kernels for Non-Parametric Independence Testing
Nathaniel Xu
Feng Liu
Danica J. Sutherland
BDL
31
0
0
10 Sep 2024
Calibration by Distribution Matching: Trainable Kernel Calibration
  Metrics
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics
Charles Marx
Sofian Zalouk
Stefano Ermon
27
6
0
31 Oct 2023
Kernelized Cumulants: Beyond Kernel Mean Embeddings
Kernelized Cumulants: Beyond Kernel Mean Embeddings
Patric Bonnier
Harald Oberhauser
Zoltan Szabo
23
5
0
29 Jan 2023
Returning The Favour: When Regression Benefits From Probabilistic Causal
  Knowledge
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge
S. Bouabid
Jake Fawkes
Dino Sejdinovic
CML
36
0
0
26 Jan 2023
Second-level global sensitivity analysis of numerical simulators with
  application to an accident scenario in a sodium-cooled fast reactor
Second-level global sensitivity analysis of numerical simulators with application to an accident scenario in a sodium-cooled fast reactor
Anouar Meynaoui
A. Marrel
Béatrice Laurent
17
4
0
21 Dec 2022
Calibration tests beyond classification
Calibration tests beyond classification
David Widmann
Fredrik Lindsten
Dave Zachariah
25
17
0
21 Oct 2022
Maximum Mean Discrepancy on Exponential Windows for Online Change Detection
Maximum Mean Discrepancy on Exponential Windows for Online Change Detection
Florian Kalinke
Marco Heyden
Edouard Fouché
Klemens Bohm
Klemens Böhm
24
0
0
25 May 2022
Learning Invariant Representations with Missing Data
Learning Invariant Representations with Missing Data
Mark Goldstein
J. Jacobsen
O. Chau
A. Saporta
A. Puli
Rajesh Ranganath
Andrew C. Miller
OOD
12
5
0
01 Dec 2021
An Asymptotic Test for Conditional Independence using Analytic Kernel
  Embeddings
An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings
M. Scetbon
Laurent Meunier
Yaniv Romano
20
9
0
28 Oct 2021
Exact Distribution-Free Hypothesis Tests for the Regression Function of
  Binary Classification via Conditional Kernel Mean Embeddings
Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings
Ambrus Tamás
Balázs Csanád Csáji
25
4
0
08 Mar 2021
Universal Robust Regression via Maximum Mean Discrepancy
Universal Robust Regression via Maximum Mean Discrepancy
Pierre Alquier
Mathieu Gerber
38
15
0
01 Jun 2020
Hard Shape-Constrained Kernel Machines
Hard Shape-Constrained Kernel Machines
Pierre-Cyril Aubin-Frankowski
Z. Szabó
18
22
0
26 May 2020
DP-MERF: Differentially Private Mean Embeddings with Random Features for
  Practical Privacy-Preserving Data Generation
DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation
Frederik Harder
Kamil Adamczewski
Mijung Park
SyDa
25
101
0
26 Feb 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
Junhyung Park
Krikamol Muandet
28
77
0
10 Feb 2020
New statistical methodology for second level global sensitivity analysis
New statistical methodology for second level global sensitivity analysis
Anouar Meynaoui
A. Marrel
Béatrice Laurent
30
14
0
19 Feb 2019
RetGK: Graph Kernels based on Return Probabilities of Random Walks
RetGK: Graph Kernels based on Return Probabilities of Random Walks
Zhen Zhang
Mianzhi Wang
Yijian Xiang
Y. Huang
A. Nehorai
14
105
0
07 Sep 2018
A Kernel Test of Goodness of Fit
A Kernel Test of Goodness of Fit
Kacper P. Chwialkowski
Heiko Strathmann
A. Gretton
BDL
104
324
0
09 Feb 2016
Measuring and testing dependence by correlation of distances
Measuring and testing dependence by correlation of distances
G. Székely
Maria L. Rizzo
N. K. Bakirov
175
2,577
0
28 Mar 2008
1