Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features

15 November 2017

Jean-François Ton

Seth Flaxman

Dino Sejdinovic

Samir Bhatt

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Papers citing "Spatial Mapping with Gaussian Processes and Nonstationary Fourier Features"

23 / 23 papers shown

Title
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability Lingfei Wu Ian En-Hsu Yen Jie Chen Rui Yan 42 37 0 14 Sep 2018
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees H. Avron Michael Kapralov Cameron Musco Christopher Musco A. Velingker A. Zandieh 71 156 0 26 Apr 2018
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 135 1,099 0 01 Nov 2017
The Error Probability of Random Fourier Features is Dimensionality Independent Jean Honorio Yu-Jun Li 27 9 0 27 Oct 2017
First-order Methods Almost Always Avoid Saddle Points Jason D. Lee Ioannis Panageas Georgios Piliouras Max Simchowitz Michael I. Jordan Benjamin Recht ODL 137 83 0 20 Oct 2017
Non-Stationary Spectral Kernels Sami Remes Markus Heinonen Samuel Kaski 63 103 0 24 May 2017
Data-driven Random Fourier Features using Stein Effect Wei-Cheng Chang Chun-Liang Li Yiming Yang Barnabás Póczós 59 30 0 23 May 2017
Improved prediction accuracy for disease risk mapping using Gaussian Process stacked generalisation Samir Bhatt E. Cameron Seth R Flaxman D. Weiss David L. Smith P. Gething 38 104 0 10 Dec 2016
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems Martín Abadi Ashish Agarwal P. Barham E. Brevdo Zhiwen Chen ... Pete Warden Martin Wattenberg Martin Wicke Yuan Yu Xiaoqiang Zheng 282 11,150 0 14 Mar 2016
A multi-resolution approximation for massive spatial datasets Matthias Katzfuss 92 245 0 16 Jul 2015
Fast Two-Sample Testing with Analytic Representations of Probability Measures Kacper P. Chwialkowski Aaditya Ramdas Dino Sejdinovic Arthur Gretton 61 155 0 15 Jun 2015
Generalized Spectral Kernels Yves-Laurent Kom Samo Stephen J. Roberts 57 57 0 07 Jun 2015
Optimal Rates for Random Fourier Features Bharath K. Sriperumbudur Z. Szabó 88 130 0 06 Jun 2015
Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs Y. Gal Richard Turner 58 78 0 09 Mar 2015
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels H. Avron Vikas Sindhwani Jiyan Yang Michael W. Mahoney 87 166 0 29 Dec 2014
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,312 0 22 Dec 2014
A la Carte - Learning Fast Kernels Zichao Yang Alex Smola Le Song A. Wilson 86 133 0 19 Dec 2014
Stochastic Gradient Hamiltonian Monte Carlo Tianqi Chen E. Fox Carlos Guestrin BDL 112 913 0 17 Feb 2014
Variational inference for sparse spectrum Gaussian process regression Linda S. L. Tan V. M. Ong David J. Nott Ajay Jasra 106 15 0 09 Jun 2013
Gaussian Process Kernels for Pattern Discovery and Extrapolation A. Wilson Ryan P. Adams GP 81 609 0 18 Feb 2013
Expectation Propagation for approximate Bayesian inference T. Minka 137 1,909 0 10 Jan 2013
Variable noise and dimensionality reduction for sparse Gaussian processes Edward Snelson Zoubin Ghahramani 107 79 0 27 Jun 2012
Practical recommendations for gradient-based training of deep architectures Yoshua Bengio 3DH ODL 193 2,201 0 24 Jun 2012