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Kernel Distribution Embeddings: Universal Kernels, Characteristic
  Kernels and Kernel Metrics on Distributions
v1v2 (latest)

Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions

18 April 2016
Carl-Johann Simon-Gabriel
Bernhard Schölkopf
ArXiv (abs)PDFHTML

Papers citing "Kernel Distribution Embeddings: Universal Kernels, Characteristic Kernels and Kernel Metrics on Distributions"

50 / 63 papers shown
Title
On relative universality, regression operator, and conditional independence
On relative universality, regression operator, and conditional independence
Bing Li
Ben Jones
A. Artemiou
50
0
0
15 Apr 2025
Towards Scalable Topological Regularizers
Towards Scalable Topological Regularizers
Hiu-Tung Wong
Darrick Lee
Hong Yan
BDL
137
0
0
24 Jan 2025
Spectral Representations for Accurate Causal Uncertainty Quantification
  with Gaussian Processes
Spectral Representations for Accurate Causal Uncertainty Quantification with Gaussian Processes
Hugh Dance
Peter Orbanz
Arthur Gretton
CML
61
1
0
18 Oct 2024
Gaussian Processes for Observational Dose-Response Inference
Gaussian Processes for Observational Dose-Response Inference
Jake R. Dailey
43
0
0
25 Sep 2024
Learning to Embed Distributions via Maximum Kernel Entropy
Learning to Embed Distributions via Maximum Kernel Entropy
Oleksii Kachaiev
Stefano Recanatesi
OOD
120
0
0
01 Aug 2024
Structurally Aware Robust Model Selection for Mixtures
Structurally Aware Robust Model Selection for Mixtures
Jiawei Li
Jonathan H. Huggins
81
0
0
01 Mar 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
Georg Manten
Cecilia Casolo
E. Ferrucci
Søren Wengel Mogensen
C. Salvi
Niki Kilbertus
CMLBDL
248
12
0
28 Feb 2024
Transfer Operators from Batches of Unpaired Points via Entropic
  Transport Kernels
Transfer Operators from Batches of Unpaired Points via Entropic Transport Kernels
F. Beier
Hancheng Bi
Clément Sarrazin
Bernhard Schmitzer
Gabriele Steidl
OT
38
2
0
13 Feb 2024
Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces
Wasserstein Gradient Flows for Moreau Envelopes of f-Divergences in Reproducing Kernel Hilbert Spaces
Viktor Stein
Sebastian Neumayer
Gabriele Steidl
Nicolaj Rux
164
11
0
07 Feb 2024
Transportation Marketplace Rate Forecast Using Signature Transform
Transportation Marketplace Rate Forecast Using Signature Transform
Haotian Gu
Xin Guo
Timothy L. Jacobs
Philip M. Kaminsky
Xinyu Li
AI4TS
50
0
0
10 Jan 2024
Optimal Transport for Kernel Gaussian Mixture Models
Optimal Transport for Kernel Gaussian Mixture Models
Jung Hun Oh
Rena Elkin
Anish K. Simhal
Jiening Zhu
Joseph O. Deasy
Allen Tannenbaum
OT
61
0
0
28 Oct 2023
Geometric Learning with Positively Decomposable Kernels
Geometric Learning with Positively Decomposable Kernels
Nathael Da Costa
Cyrus Mostajeran
Juan-Pablo Ortega
Salem Said
64
3
0
20 Oct 2023
Spectral Regularized Kernel Goodness-of-Fit Tests
Spectral Regularized Kernel Goodness-of-Fit Tests
Omar Hagrass
Bharath K. Sriperumbudur
Bing Li
143
4
0
08 Aug 2023
Kernel-Based Testing for Single-Cell Differential Analysis
Kernel-Based Testing for Single-Cell Differential Analysis
Anthony Ozier-Lafontaine
Camille Fourneaux
G. Durif
Polina Arsenteva
C. Vallot
O. Gandrillon
Sandrine Giraud
Bertrand Michel
Franck Picard
55
5
0
17 Jul 2023
Non-parametric online market regime detection and regime clustering for
  multidimensional and path-dependent data structures
Non-parametric online market regime detection and regime clustering for multidimensional and path-dependent data structures
Zacharia Issa
Blanka Horvath
97
4
0
27 Jun 2023
Non-adversarial training of Neural SDEs with signature kernel scores
Non-adversarial training of Neural SDEs with signature kernel scores
Zacharia Issa
Blanka Horvath
M. Lemercier
C. Salvi
AI4TS
116
26
0
25 May 2023
Estimation Beyond Data Reweighting: Kernel Method of Moments
Estimation Beyond Data Reweighting: Kernel Method of Moments
Heiner Kremer
Yassine Nemmour
Bernhard Schölkopf
Jia-Jie Zhu
103
7
0
18 May 2023
Efficient Convex Algorithms for Universal Kernel Learning
Efficient Convex Algorithms for Universal Kernel Learning
Aleksandr Talitckii
Brendon K. Colbert
Matthew M. Peet
16
1
0
15 Apr 2023
Robustifying likelihoods by optimistically re-weighting data
Robustifying likelihoods by optimistically re-weighting data
Miheer Dewaskar
Christopher Tosh
Jeremias Knoblauch
David B. Dunson
93
6
0
19 Mar 2023
Reproducing kernel Hilbert spaces in the mean field limit
Reproducing kernel Hilbert spaces in the mean field limit
Christian Fiedler
Michael Herty
M. Rom
C. Segala
Sebastian Trimpe
71
6
0
28 Feb 2023
Spectral Regularized Kernel Two-Sample Tests
Spectral Regularized Kernel Two-Sample Tests
Omar Hagrass
Bharath K. Sriperumbudur
Bing Li
78
15
0
19 Dec 2022
Targeted Separation and Convergence with Kernel Discrepancies
Targeted Separation and Convergence with Kernel Discrepancies
Alessandro Barp
Carl-Johann Simon-Gabriel
Mark Girolami
Lester W. Mackey
149
15
0
26 Sep 2022
Ensemble forecasts in reproducing kernel Hilbert space family
Ensemble forecasts in reproducing kernel Hilbert space family
Benjamin Dufée
Berenger Hug
É. Mémin
G. Tissot
138
1
0
29 Jul 2022
Learning Counterfactually Invariant Predictors
Learning Counterfactually Invariant Predictors
Francesco Quinzan
Cecilia Casolo
Krikamol Muandet
Yucen Luo
Niki Kilbertus
118
10
0
20 Jul 2022
Characteristic kernels on Hilbert spaces, Banach spaces, and on sets of
  measures
Characteristic kernels on Hilbert spaces, Banach spaces, and on sets of measures
Johanna Fasciati-Ziegel
D. Ginsbourger
L. Dümbgen
VLM
30
6
0
15 Jun 2022
Robust Flow-based Conformal Inference (FCI) with Statistical Guarantee
Robust Flow-based Conformal Inference (FCI) with Statistical Guarantee
Youhui Ye
Meimei Liu
Xin Xing
59
0
0
22 May 2022
On boundary conditions parametrized by analytic functions
On boundary conditions parametrized by analytic functions
Markus Lange-Hegermann
D. Robertz
54
5
0
06 May 2022
Kernel Robust Hypothesis Testing
Kernel Robust Hypothesis Testing
Zhongchang Sun
Shaofeng Zou
OOD
77
13
0
23 Mar 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive
  Agents
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents
Alessandro Barp
Lancelot Da Costa
G. Francca
Karl J. Friston
Mark Girolami
Michael I. Jordan
G. Pavliotis
97
25
0
20 Mar 2022
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint
  Support
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support
Pierre Glaser
Michael Arbel
Arthur Gretton
131
40
0
16 Jun 2021
Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions,
  Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey
Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey
Benyamin Ghojogh
A. Ghodsi
Fakhri Karray
Mark Crowley
72
37
0
15 Jun 2021
Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and
  Depth in Functional Data Analysis
Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and Depth in Functional Data Analysis
George Wynne
Stanislav Nagy
103
6
0
26 May 2021
Robust Sample Weighting to Facilitate Individualized Treatment Rule
  Learning for a Target Population
Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target Population
Rui Chen
J. Huling
Guanhua Chen
Menggang Yu
CML
64
1
0
03 May 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean
  Embeddings and U-Statistic Regression
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
Junhyung Park
Uri Shalit
Bernhard Schölkopf
Krikamol Muandet
CML
115
33
0
16 Feb 2021
Handling Hard Affine SDP Shape Constraints in RKHSs
Handling Hard Affine SDP Shape Constraints in RKHSs
Pierre-Cyril Aubin-Frankowski
Z. Szabó
49
7
0
05 Jan 2021
Glucose values prediction five years ahead with a new framework of
  missing responses in reproducing kernel Hilbert spaces, and the use of
  continuous glucose monitoring technology
Glucose values prediction five years ahead with a new framework of missing responses in reproducing kernel Hilbert spaces, and the use of continuous glucose monitoring technology
Marcos Matabuena
Paulo Félix
C. Meijide-García
F. Gudé
105
0
0
11 Dec 2020
Kernel Mean Embedding of Probability Measures and its Applications to
  Functional Data Analysis
Kernel Mean Embedding of Probability Measures and its Applications to Functional Data Analysis
Saeed Hayati
Kenji Fukumizu
A. Parvardeh
22
5
0
04 Nov 2020
Instrumental Variable Regression via Kernel Maximum Moment Loss
Instrumental Variable Regression via Kernel Maximum Moment Loss
Rui Zhang
Masaaki Imaizumi
Bernhard Schölkopf
Krikamol Muandet
91
9
0
15 Oct 2020
Unbalanced Sobolev Descent
Unbalanced Sobolev Descent
Youssef Mroueh
Mattia Rigotti
70
17
0
29 Sep 2020
A Kernel Two-Sample Test for Functional Data
A Kernel Two-Sample Test for Functional Data
George Wynne
Andrew B. Duncan
99
45
0
25 Aug 2020
Path Signatures on Lie Groups
Path Signatures on Lie Groups
Darrick Lee
Robert Ghrist
78
8
0
02 Jul 2020
Distributional Random Forests: Heterogeneity Adjustment and Multivariate
  Distributional Regression
Distributional Random Forests: Heterogeneity Adjustment and Multivariate Distributional Regression
Domagoj Cevid
Loris Michel
Jeffrey Näf
N. Meinshausen
Peter Buhlmann
96
43
0
29 May 2020
Hard Shape-Constrained Kernel Machines
Hard Shape-Constrained Kernel Machines
Pierre-Cyril Aubin-Frankowski
Z. Szabó
62
22
0
26 May 2020
Generalized Energy Based Models
Generalized Energy Based Models
Michael Arbel
Liang Zhou
Arthur Gretton
DRL
179
81
0
10 Mar 2020
Kernel Conditional Moment Test via Maximum Moment Restriction
Kernel Conditional Moment Test via Maximum Moment Restriction
Krikamol Muandet
Wittawat Jitkrittum
Jonas M. Kubler
54
25
0
21 Feb 2020
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application
  to Bayesian (Combinatorial) Optimization
Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Poompol Buathong
D. Ginsbourger
Tipaluck Krityakierne
BDL
97
22
0
09 Oct 2019
Comparing distributions: $\ell_1$ geometry improves kernel two-sample
  testing
Comparing distributions: ℓ1\ell_1ℓ1​ geometry improves kernel two-sample testing
M. Scetbon
Gaël Varoquaux
61
10
0
19 Sep 2019
Asymptotically Optimal One- and Two-Sample Testing with Kernels
Asymptotically Optimal One- and Two-Sample Testing with Kernels
Shengyu Zhu
Biao Chen
Zhitang Chen
Pengfei Yang
78
7
0
27 Aug 2019
Bayesian Learning from Sequential Data using Gaussian Processes with
  Signature Covariances
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
Csaba Tóth
Harald Oberhauser
48
9
0
19 Jun 2019
A Reproducing Kernel Hilbert Space log-rank test for the two-sample
  problem
A Reproducing Kernel Hilbert Space log-rank test for the two-sample problem
T. Fernandez
Nicolás Rivera
39
8
0
10 Apr 2019
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