Fast methods for training Gaussian processes on large data sets

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Fast methods for training Gaussian processes on large data sets

5 April 2016

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Papers citing "Fast methods for training Gaussian processes on large data sets"

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Title
Vanilla Bayesian Optimization Performs Great in High Dimensions Carl Hvarfner E. Hellsten Luigi Nardi 80 28 0 03 Feb 2024
LABCAT: Locally adaptive Bayesian optimization using principal-component-aligned trust regions E. Visser C. E. V. Daalen J. C. Schoeman 74 0 0 19 Nov 2023
Online and Adaptive Parking Availability Mapping: An Uncertainty-Aware Active Sensing Approach for Connected Vehicles Luca Varotto Angelo Cenedese 13 0 0 01 May 2021
Model Learning with Personalized Interpretability Estimation (ML-PIE) M. Virgolin A. D. Lorenzo Francesca Randone Eric Medvet M. Wahde 101 31 0 13 Apr 2021
The Promises and Pitfalls of Deep Kernel Learning Sebastian W. Ober C. Rasmussen Mark van der Wilk UQCV BDL 82 109 0 24 Feb 2021
Physics of eccentric binary black hole mergers: A numerical relativity perspective Eliu A. Huerta Roland Haas Sarah Habib Anushri Gupta A. Rebei ... S. Rosofsky E. Wessel B. Agarwal Diyu Luo W. Ren 26 23 0 21 Jan 2019
Surrogate-assisted parallel tempering for Bayesian neural learning Rohitash Chandra Konark Jain Arpit Kapoor Ashray Aman BDL 43 8 0 21 Nov 2018