Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression

3 June 2018

Jianfei Cai

Papers citing "Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression"

37 / 37 papers shown

Title
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functions Gledson Rodrigo Tondo I. Kavrakov Guido Morgenthal 55 2 0 13 Mar 2025
Decentralized Online Ensembles of Gaussian Processes for Multi-Agent Systems Fernando Llorente Daniel Waxman Petar M. Djurić 43 0 0 07 Feb 2025
GPTreeO: An R package for continual regression with dividing local Gaussian processes Timo Braun Anders Kvellestad Riccardo De Bin 18 0 0 01 Oct 2024
Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Wireless Sensor Networks Xingchi Liu Lyudmila Mihaylova Jemin George T. Pham 40 9 0 11 Sep 2024
Aggregation Models with Optimal Weights for Distributed Gaussian Processes Liam Hebert Sukhdeep S. Sodhi 27 0 0 01 Aug 2024
3D Uncertain Implicit Surface Mapping using GMM and GP Qianqian Zou Monika Sester 3DV 28 1 0 12 Mar 2024
A Bayesian Committee Machine Potential for Oxygen-containing Organic Compounds Seungwon Kim D. C. Yang S. Y. Willow Chang Woo Myung 20 0 0 02 Mar 2024
Whom to Trust? Elective Learning for Distributed Gaussian Process Regression Zewen Yang X. Dai Akshat Dubey Sandra Hirche Georges Hattab 20 10 0 05 Feb 2024
Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space Mohsin Hasan Guojun Zhang Kaiyang Guo Xi Chen Pascal Poupart FedML 34 9 0 15 Dec 2023
Resource-Efficient Cooperative Online Scalar Field Mapping via Distributed Sparse Gaussian Process Regression Tianyi Ding Ronghao Zheng Senlin Zhang Meiqin Liu 28 1 0 19 Sep 2023
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression Robert Allison Anthony Stephenson F. Samuel Edward O. Pyzer-Knapp UQCV 17 3 0 26 Jun 2023
Bayesian data fusion with shared priors Peng Wu Tales Imbiriba Victor Elvira Pau Closas FedML 34 6 0 14 Dec 2022
Gaussian Process Mapping of Uncertain Building Models with GMM as Prior Qianqian Zou C. Brenner Monika Sester 16 2 0 14 Dec 2022
Entry Dependent Expert Selection in Distributed Gaussian Processes Using Multilabel Classification Hamed Jalali Gjergji Kasneci 16 0 0 17 Nov 2022
Hierarchical Policy Blending as Inference for Reactive Robot Control Kay Hansel Julen Urain Jan Peters Georgia Chalvatzaki 37 15 0 14 Oct 2022
Mixtures of Gaussian Process Experts with SMC $^2$ Teemu Härkönen S. Wade K. Law L. Roininen 14 2 0 26 Aug 2022
Fully Decentralized, Scalable Gaussian Processes for Multi-Agent Federated Learning George P. Kontoudis D. Stilwell FedML 8 8 0 06 Mar 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
Gaussian Graphical Models as an Ensemble Method for Distributed Gaussian Processes Hamed Jalali Gjergji Kasneci FedML 19 0 0 07 Feb 2022
Correlated Product of Experts for Sparse Gaussian Process Regression Manuel Schürch Dario Azzimonti A. Benavoli Marco Zaffalon 16 12 0 17 Dec 2021
Learning with Subset Stacking Ilker Birbil S. Yıldırım Kaya Gökalp Hakan Akyüz 23 0 0 12 Dec 2021
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems Haitao Liu Changjun Liu Xiaomo Jiang Xudong Chen Shuhua Yang Xiaofang Wang BDL AI4TS 32 2 0 03 Jun 2021
Lightweight Distributed Gaussian Process Regression for Online Machine Learning Zhenyuan Yuan Minghui Zhu 21 4 0 11 May 2021
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
Temporal Gaussian Process Regression in Logarithmic Time Adrien Corenflos Zheng Zhao Simo Särkkä 17 3 0 19 Feb 2021
Healing Products of Gaussian Processes Samuel N. Cohen R. Mbuvha T. Marwala M. Deisenroth GP 16 0 0 14 Feb 2021
Gaussian Experts Selection using Graphical Models Hamed Jalali Martin Pawelczyk Gjerji Kasneci 14 3 0 02 Feb 2021
Aggregating Dependent Gaussian Experts in Local Approximation Hamed Jalali Gjergji Kasneci 19 4 0 17 Oct 2020
Modulating Scalable Gaussian Processes for Expressive Statistical Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang 13 4 0 29 Aug 2020
Deep Latent-Variable Kernel Learning Haitao Liu Yew-Soon Ong Xiaomo Jiang Xiaofang Wang BDL 12 8 0 18 May 2020
Financial Applications of Gaussian Processes and Bayesian Optimization Joan Gonzalvez Edmond Lezmi T. Roncalli Jiali Xu 20 54 0 12 Mar 2019
Large-scale Heteroscedastic Regression via Gaussian Process Haitao Liu Yew-Soon Ong Jianfei Cai BDL 21 26 0 03 Nov 2018
Understanding and Comparing Scalable Gaussian Process Regression for Big Data Haitao Liu Jianfei Cai Yew-Soon Ong Yi Wang 27 24 0 03 Nov 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 16 681 0 03 Jul 2018
Embarrassingly Parallel Inference for Gaussian Processes M. Zhang Sinead Williamson 18 24 0 27 Feb 2017
Cluster-based Kriging Approximation Algorithms for Complexity Reduction Bas van Stein Hao Wang W. Kowalczyk M. Emmerich Thomas Bäck 46 45 0 04 Feb 2017
A Framework for Evaluating Approximation Methods for Gaussian Process Regression Krzysztof Chalupka Christopher K. I. Williams Iain Murray GP 71 169 0 29 May 2012