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

18 April 2016

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 Bing Li Ben Jones A. Artemiou 52 0 0 15 Apr 2025
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 Hugh Dance Peter Orbanz Arthur Gretton CML 61 1 0 18 Oct 2024
Gaussian Processes for Observational Dose-Response Inference Jake R. Dailey 45 0 0 25 Sep 2024
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 Jiawei Li Jonathan H. Huggins 81 0 0 01 Mar 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten Cecilia Casolo E. Ferrucci Søren Wengel Mogensen C. Salvi Niki Kilbertus CML BDL 248 12 0 28 Feb 2024
Transfer Operators from Batches of Unpaired Points via Entropic Transport Kernels F. Beier Hancheng Bi Clément Sarrazin Bernhard Schmitzer Gabriele Steidl OT 40 2 0 13 Feb 2024
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 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 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 Nathael Da Costa Cyrus Mostajeran Juan-Pablo Ortega Salem Said 64 3 0 20 Oct 2023
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 Anthony Ozier-Lafontaine Camille Fourneaux G. Durif Polina Arsenteva C. Vallot O. Gandrillon Sandrine Giraud Bertrand Michel Franck Picard 55 6 0 17 Jul 2023
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 Zacharia Issa Blanka Horvath M. Lemercier C. Salvi AI4TS 116 26 0 25 May 2023
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 Aleksandr Talitckii Brendon K. Colbert Matthew M. Peet 18 1 0 15 Apr 2023
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 Christian Fiedler Michael Herty M. Rom C. Segala Sebastian Trimpe 71 6 0 28 Feb 2023
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 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 Benjamin Dufée Berenger Hug É. Mémin G. Tissot 138 1 0 29 Jul 2022
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 Johanna Fasciati-Ziegel D. Ginsbourger L. Dümbgen VLM 32 6 0 15 Jun 2022
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 Markus Lange-Hegermann D. Robertz 54 5 0 06 May 2022
Kernel Robust Hypothesis Testing Zhongchang Sun Shaofeng Zou OOD 77 13 0 23 Mar 2022
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 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 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 George Wynne Stanislav Nagy 103 6 0 26 May 2021
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 Junhyung Park Uri Shalit Bernhard Schölkopf Krikamol Muandet CML 115 33 0 16 Feb 2021
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 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 Saeed Hayati Kenji Fukumizu A. Parvardeh 24 5 0 04 Nov 2020
Instrumental Variable Regression via Kernel Maximum Moment Loss Rui Zhang Masaaki Imaizumi Bernhard Schölkopf Krikamol Muandet 93 9 0 15 Oct 2020
Unbalanced Sobolev Descent Youssef Mroueh Mattia Rigotti 70 17 0 29 Sep 2020
A Kernel Two-Sample Test for Functional Data George Wynne Andrew B. Duncan 99 45 0 25 Aug 2020
Path Signatures on Lie Groups Darrick Lee Robert Ghrist 78 8 0 02 Jul 2020
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 Pierre-Cyril Aubin-Frankowski Z. Szabó 62 22 0 26 May 2020
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 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 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: $\ell_1$ 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 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 Csaba Tóth Harald Oberhauser 48 9 0 19 Jun 2019
A Reproducing Kernel Hilbert Space log-rank test for the two-sample problem T. Fernandez Nicolás Rivera 41 8 0 10 Apr 2019