Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models

6 February 2014

Papers citing "Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models"

22 / 22 papers shown

Title
Memory Safe Computations with XLA Compiler A. Artemev Tilman Roeder Mark van der Wilk 29 8 0 28 Jun 2022
Fast Gaussian Process Posterior Mean Prediction via Local Cross Validation and Precomputation Alec M. Dunton Benjamin W. Priest Amanda Muyskens GP 32 3 0 22 May 2022
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains Haitao Liu Kai Wu Yew-Soon Ong Chao Bian Xiaomo Jiang Xiaofang Wang 19 7 0 25 Feb 2022
Adaptive Cholesky Gaussian Processes Simon Bartels Kristoffer Stensbo-Smidt Pablo Moreno-Muñoz Wouter Boomsma J. Frellsen Søren Hauberg 33 3 0 22 Feb 2022
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey Kai Chen Qinglei Kong Yijue Dai Yue Xu Feng Yin Lexi Xu Shuguang Cui 35 30 0 18 Mar 2021
Implicit Posterior Variational Inference for Deep Gaussian Processes Haibin Yu Yizhou Chen Zhongxiang Dai K. H. Low Patrick Jaillet 19 42 0 26 Oct 2019
Online Anomaly Detection with Sparse Gaussian Processes Jingjing Fei Shiliang Sun AI4TS 21 20 0 14 May 2019
Structured Bayesian Gaussian process latent variable model: applications to data-driven dimensionality reduction and high-dimensional inversion Steven Atkinson N. Zabaras 16 36 0 11 Jul 2018
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression Haitao Liu Jianfei Cai Yi Wang Yew-Soon Ong 23 83 0 03 Jun 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models K. Krauth Edwin V. Bonilla Kurt Cutajar Maurizio Filippone GP BDL 16 54 0 18 Oct 2016
Chained Gaussian Processes Alan D. Saul J. Hensman Aki Vehtari Neil D. Lawrence 16 59 0 18 Apr 2016
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis Andreas C. Damianou Neil D. Lawrence Carl Henrik Ek 16 12 0 17 Apr 2016
System Identification through Online Sparse Gaussian Process Regression with Input Noise Hildo Bijl Thomas B. Schon J. Wingerden M. Verhaegen 39 41 0 29 Jan 2016
Variational Auto-encoded Deep Gaussian Processes Zhenwen Dai Andreas C. Damianou Javier I. González Neil D. Lawrence BDL 24 131 0 19 Nov 2015
Bayesian Optimization with Dimension Scheduling: Application to Biological Systems Doniyor Ulmasov C. Baroukh Benoît Chachuat M. Deisenroth Ruth Misener 23 40 0 17 Nov 2015
Gaussian Process Random Fields David A. Moore Stuart J. Russell GP 19 19 0 31 Oct 2015
Blitzkriging: Kronecker-structured Stochastic Gaussian Processes T. Nickson Tom Gunter C. Lloyd Michael A. Osborne Stephen J. Roberts 19 21 0 27 Oct 2015
Mondrian Forests for Large-Scale Regression when Uncertainty Matters Balaji Lakshminarayanan Daniel M. Roy Yee Whye Teh UQCV 26 56 0 11 Jun 2015
Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency Inputs Y. Gal Richard Turner 21 78 0 09 Mar 2015
Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression Jun Wei Ng M. Deisenroth 31 51 0 09 Dec 2014
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models Andreas C. Damianou Michalis K. Titsias Neil D. Lawrence 41 25 0 08 Sep 2014