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Marginalizing Gaussian Process Hyperparameters using Sequential Monte
  Carlo
v1v2 (latest)

Marginalizing Gaussian Process Hyperparameters using Sequential Monte Carlo

6 February 2015
Andreas Svensson
J. Dahlin
Thomas B. Schon
    GP
ArXiv (abs)PDFHTML

Papers citing "Marginalizing Gaussian Process Hyperparameters using Sequential Monte Carlo"

10 / 10 papers shown
Bayesian autoregression to optimize temporal Matérn kernel Gaussian process hyperparameters
Bayesian autoregression to optimize temporal Matérn kernel Gaussian process hyperparameters
Wouter M. Kouw
BDLGP
228
0
0
13 Aug 2025
Bayesian grey-box identification of nonlinear convection effects in heat
  transfer dynamics
Bayesian grey-box identification of nonlinear convection effects in heat transfer dynamics
Wouter M. Kouw
Caspar Gruijthuijsen
Lennart Blanken
Enzo Evers
Timothy Rogers
226
1
0
01 Jul 2024
Robust Inference of Dynamic Covariance Using Wishart Processes and
  Sequential Monte Carlo
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte CarloEntropy (Entropy), 2024
Hester Huijsdens
D. Leeftink
Linda Geerligs
Max Hinne
331
1
0
07 Jun 2024
Online Student-$t$ Processes with an Overall-local Scale Structure for
  Modelling Non-stationary Data
Online Student-ttt Processes with an Overall-local Scale Structure for Modelling Non-stationary DataInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Taole Sha
Michael Minyi Zhang
273
0
0
01 Nov 2023
Mixtures of Gaussian Process Experts with SMC$^2$
Mixtures of Gaussian Process Experts with SMC2^22
Teemu Härkönen
S. Wade
K. Law
L. Roininen
321
3
0
26 Aug 2022
A Bayesian Approach To Graph Partitioning
A Bayesian Approach To Graph Partitioning
Farshad Noravesh
204
0
0
24 Apr 2022
Increasing the efficiency of Sequential Monte Carlo samplers through the
  use of approximately optimal L-kernels
Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels
P. L. Green
Robert E. Moore
Ryan J Jackson
Jinglai Li
Simon Maskell
273
15
0
24 Apr 2020
Sequential Gaussian Processes for Online Learning of Nonstationary
  Functions
Sequential Gaussian Processes for Online Learning of Nonstationary FunctionsIEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2019
M. Zhang
Bianca Dumitrascu
Sinead Williamson
Barbara E. Engelhardt
755
10
0
24 May 2019
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes
  Regression for Time Series
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series
Feng Yin
Lishuo Pan
Xinwei He
Tianshi Chen
Sergios Theodoridis
Zhi-Quan
Jianfeng Yao
AI4TS
194
35
0
21 Apr 2019
Ensemble Kalman Filtering for Online Gaussian Process Regression and
  Learning
Ensemble Kalman Filtering for Online Gaussian Process Regression and Learning
Danil Kuzin
Le Yang
Olga Isupova
Lyudmila Mihaylova
211
7
0
09 Jul 2018
1
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