Gaussian Processes on Distributions based on Regularized Optimal Transport

12 October 2022

Papers citing "Gaussian Processes on Distributions based on Regularized Optimal Transport"

9 / 9 papers shown

Title
Improved learning theory for kernel distribution regression with two-stage sampling F. Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes 96 1 0 28 Jan 2025
Wasserstein Spatial Depth F. Bachoc Alberto González Sanz Jean-Michel Loubes Yisha Yao 40 1 0 16 Nov 2024
Learning signals defined on graphs with optimal transport and Gaussian process regression Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 30 1 0 21 Oct 2024
Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs Lucas Reding A. F. López-Lopera F. Bachoc 36 1 0 26 Apr 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 30 4 0 06 Feb 2024
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks Felix Jimenez Matthias Katzfuss BDL UQCV 61 1 0 26 May 2023
A Unified Framework for Implicit Sinkhorn Differentiation Marvin Eisenberger Aysim Toker Laura Leal-Taixé Florian Bernard Daniel Cremers AI4CE 48 23 0 13 May 2022
Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein Marco Cuturi Laetitia Meng-Papaxanthos Yingtao Tian Charlotte Bunne Geoff Davis O. Teboul OT 143 94 0 28 Jan 2022
Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes F. Bachoc 45 57 0 18 Jan 2013