Multiresolution Kernel Approximation for Gaussian Process Regression

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Multiresolution Kernel Approximation for Gaussian Process Regression

7 August 2017

Jonathan Eskreis-Winkler

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Papers citing "Multiresolution Kernel Approximation for Gaussian Process Regression"

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Title
Spatially scalable recursive estimation of Gaussian process terrain maps using local basis functions Frida Marie Viset Rudy Helmons Manon Kok 96 1 0 17 Oct 2022
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction Yi Ding Avinash Rao Hyebin Song Rebecca Willett Henry Hoffmann 95 3 0 16 Mar 2022
Construction and Monte Carlo estimation of wavelet frames generated by a reproducing kernel Ernesto De Vito Ž. Kereta Valeriya Naumova Lorenzo Rosasco Stefano Vigogna 72 3 0 17 Jun 2020
Multiresolution Tensor Learning for Efficient and Interpretable Spatial Analysis Jung Yeon Park K. T. Carr Stephan Zhang Yisong Yue Rose Yu 109 14 0 13 Feb 2020
Spatial Analysis Made Easy with Linear Regression and Kernels Philip Milton E. Giorgi Samir Bhatt 55 20 0 22 Feb 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 100 10 0 18 Dec 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 144 697 0 03 Jul 2018
Scalable Gaussian Process Inference with Finite-data Mean and Variance Guarantees Jonathan H. Huggins Trevor Campbell Mikolaj Kasprzak Tamara Broderick 89 15 0 26 Jun 2018