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A Gaussian Process Regression Model for Distribution Inputs

31 January 2017

Papers citing "A Gaussian Process Regression Model for Distribution Inputs"

26 / 26 papers shown

Title
Distributional encoding for Gaussian process regression with qualitative inputs Sébastien Da Veiga UQCV 95 0 0 05 Jun 2025
Improved learning theory for kernel distribution regression with two-stage sampling François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes 145 2 0 28 Jan 2025
Adaptive Residual Transformation for Enhanced Feature-Based OOD Detection in SAR Imagery Kyung-Hwan Lee Kyung-Tae Kim 77 0 0 01 Nov 2024
Learning to Embed Distributions via Maximum Kernel Entropy Oleksii Kachaiev Stefano Recanatesi OOD 120 0 0 01 Aug 2024
Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs Lucas Reding A. F. López-Lopera François Bachoc 70 1 0 26 Apr 2024
Gaussian Process regression over discrete probability measures: on the non-stationarity relation between Euclidean and Wasserstein Squared Exponential Kernels Antonio Candelieri Andrea Ponti Francesco Archetti 88 1 0 02 Dec 2022
Gaussian Processes on Distributions based on Regularized Optimal Transport François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 66 8 0 12 Oct 2022
Computationally-efficient initialisation of GPs: The generalised variogram method Felipe A. Tobar Elsa Cazelles T. Wolff 47 0 0 11 Oct 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 100 0 0 27 Jun 2022
Multivariate Gaussian Random Fields over Generalized Product Spaces involving the Hypertorus François Bachoc A. Peron Emilio Porcu 36 3 0 22 Feb 2022
Distribution Regression with Sliced Wasserstein Kernels Dimitri Meunier Massimiliano Pontil C. Ciliberto OOD 61 17 0 08 Feb 2022
Learning System Parameters from Turing Patterns David Schnörr Christoph Schnörr 13 11 0 19 Aug 2021
Marginalising over Stationary Kernels with Bayesian Quadrature Saad Hamid Sebastian Schulze Michael A. Osborne Stephen J. Roberts GP 55 4 0 14 Jun 2021
Central Limit Theorems for General Transportation Costs E. del Barrio Alberto González Sanz Jean-Michel Loubes OT 62 28 0 12 Feb 2021
Kernel-based ANOVA decomposition and Shapley effects -- Application to global sensitivity analysis Sébastien Da Veiga FAtt 72 26 0 14 Jan 2021
Hierarchical Gaussian Processes with Wasserstein-2 Kernels S. Popescu D. Sharp James H. Cole Ben Glocker 74 5 0 28 Oct 2020
The statistical effect of entropic regularization in optimal transportation E. del Barrio Jean-Michel Loubes OT 78 22 0 09 Jun 2020
Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes François Bachoc José Bétancourt Reinhard Furrer T. Klein 45 12 0 25 Nov 2019
Deep Kernels with Probabilistic Embeddings for Small-Data Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han BDL UQCV 44 8 0 13 Oct 2019
Dataset2Vec: Learning Dataset Meta-Features H. Jomaa Lars Schmidt-Thieme Josif Grabocka SSL 86 64 0 27 May 2019
Aggregated kernel based tests for signal detection in a regression model T. T. T. Bui 16 0 0 05 Apr 2019
Explaining Machine Learning Models using Entropic Variable Projection François Bachoc Fabrice Gamboa Max Halford Jean-Michel Loubes Laurent Risser FAtt 63 5 0 18 Oct 2018
Improving Temporal Interpolation of Head and Body Pose using Gaussian Process Regression in a Matrix Completion Setting Stephanie Tan Hayley Hung 43 4 0 06 Aug 2018
Domain2Vec: Deep Domain Generalization A. Deshmukh Ankit Bansal Akash Rastogi ViT OOD 53 5 0 09 Jul 2018
Distribution regression model with a Reproducing Kernel Hilbert Space approach T. T. T. Bui Jean-Michel Loubes Risser Balaresque 48 11 0 27 Jun 2018
Gaussian Processes indexed on the symmetric group: prediction and learning François Bachoc Baptiste Broto Fabrice Gamboa Jean-Michel Loubes 38 0 0 16 Mar 2018