Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains

25 February 2022

Papers citing "Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains"

23 / 23 papers shown

Title
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization Haitao Liu Jiaqi Ding Xinyu Xie Xiaomo Jiang Yusong Zhao Xiaofang Wang BDL 48 16 0 20 Sep 2021
Transferring model structure in Bayesian transfer learning for Gaussian process regression Milan Papez A. Quinn 41 11 0 18 Jan 2021
Sparse Gaussian Process Variational Autoencoders Matthew Ashman Jonathan So Will Tebbutt Vincent Fortuin Michael Pearce Richard Turner 98 35 0 20 Oct 2020
Lateral Force Prediction using Gaussian Process Regression for Intelligent Tire Systems B. Barbosa N. Xu H. Askari A. Khajepour 33 26 0 25 Sep 2020
Multi-fidelity modeling with different input domain definitions using Deep Gaussian Processes Ali Hebbal Loïc Brevault M. Balesdent El-Ghazali Talbi N. Melab AI4CE 56 36 0 29 Jun 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 393 10,591 0 17 Feb 2020
A Comprehensive Survey on Transfer Learning Fuzhen Zhuang Zhiyuan Qi Keyu Duan Dongbo Xi Yongchun Zhu Hengshu Zhu Hui Xiong Qing He 181 4,449 0 07 Nov 2019
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels Massimiliano Patacchiola Jack Turner Elliot J. Crowley Michael F. P. O'Boyle Amos Storkey BDL 37 19 0 11 Oct 2019
Multi-Output Convolution Spectral Mixture for Gaussian Processes Kai Chen Twan van Laarhoven P. Groot Jinsong Chen E. Marchiori 41 11 0 07 Aug 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 87 690 0 03 Jul 2018
Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression Haitao Liu Jianfei Cai Yi Wang Yew-Soon Ong 57 83 0 03 Jun 2018
Heterogeneous Multi-output Gaussian Process Prediction P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 57 72 0 19 May 2018
The Gaussian Process Autoregressive Regression Model (GPAR) James Requeima Will Tebbutt W. Bruinsma Richard Turner 97 41 0 20 Feb 2018
Tensor Regression Meets Gaussian Processes Rose Yu Max Guangyu Li Yan Liu BDL 31 32 0 31 Oct 2017
Spectral Mixture Kernels for Multi-Output Gaussian Processes Gabriel Parra Felipe A. Tobar 38 79 0 05 Sep 2017
GPflow: A Gaussian process library using TensorFlow A. G. Matthews Mark van der Wilk T. Nickson Keisuke Fujii A. Boukouvalas Pablo León-Villagrá Zoubin Ghahramani J. Hensman GP 78 666 0 27 Oct 2016
Minimax Error of Interpolation and Optimal Design of Experiments for Variable Fidelity Data Alexey Zaytsev Evgeny Burnaev 56 2 0 21 Oct 2016
Deep Transfer Learning with Joint Adaptation Networks Mingsheng Long Hanhua Zhu Jianmin Wang Michael I. Jordan TTA 93 2,457 0 21 May 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models Y. Gal Mark van der Wilk C. Rasmussen 70 150 0 06 Feb 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 107 1,232 0 26 Sep 2013
Recursive co-kriging model for Design of Computer experiments with multiple levels of fidelity with an application to hydrodynamic Loic Le Gratiet AI4CE 121 295 0 02 Oct 2012
Kernels for Vector-Valued Functions: a Review Mauricio A. Alvarez Lorenzo Rosasco Neil D. Lawrence GP 207 927 0 30 Jun 2011