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Learning non-Gaussian Time Series using the Box-Cox Gaussian Process

Learning non-Gaussian Time Series using the Box-Cox Gaussian Process

19 March 2018
Gonzalo Rios
Felipe A. Tobar
    GP
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Papers citing "Learning non-Gaussian Time Series using the Box-Cox Gaussian Process"

7 / 7 papers shown
Title
Monte Carlo inference for semiparametric Bayesian regression
Monte Carlo inference for semiparametric Bayesian regression
Daniel R. Kowal
Bo-Hong Wu
22
1
0
08 Jun 2023
Computationally-efficient initialisation of GPs: The generalised
  variogram method
Computationally-efficient initialisation of GPs: The generalised variogram method
Felipe A. Tobar
Elsa Cazelles
T. Wolff
19
0
0
11 Oct 2022
Online Calibrated and Conformal Prediction Improves Bayesian
  Optimization
Online Calibrated and Conformal Prediction Improves Bayesian Optimization
Shachi Deshpande
Charles Marx
Volodymyr Kuleshov
13
7
0
08 Dec 2021
Bayesian Reconstruction of Fourier Pairs
Bayesian Reconstruction of Fourier Pairs
Felipe A. Tobar
Lerko Araya-Hernández
P. Huijse
Petar M. Djurić
25
5
0
09 Nov 2020
Transport Gaussian Processes for Regression
Transport Gaussian Processes for Regression
Gonzalo Rios
GP
26
6
0
30 Jan 2020
Compositionally-Warped Gaussian Processes
Compositionally-Warped Gaussian Processes
Gonzalo Rios
Felipe A. Tobar
19
41
0
23 Jun 2019
Low-pass filtering as Bayesian inference
Low-pass filtering as Bayesian inference
Cristobal Valenzuela
Felipe A. Tobar
AI4TS
19
2
0
09 Feb 2019
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