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Spectral Mixture Kernels for Multi-Output Gaussian Processes

5 September 2017

Papers citing "Spectral Mixture Kernels for Multi-Output Gaussian Processes"

40 / 40 papers shown

Title
Spectral Mixture Kernels for Bayesian Optimization Yi Zhang Cheng Hua GP 54 0 0 23 May 2025
PolyMicros: Bootstrapping a Foundation Model for Polycrystalline Material Structure Michael Buzzy Andreas E. Robertson Peng Chen Surya R. Kalidindi AI4CE 13 0 0 22 May 2025
Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes Jingyi Gao Seokhyun Chung FedML 55 0 0 24 Jul 2024
Scalable Multi-Output Gaussian Processes with Stochastic Variational Inference Xiaoyu Jiang Sokratia Georgaka Magnus Rattray Mauricio A. Alvarez 62 0 0 02 Jul 2024
A spectrum of physics-informed Gaussian processes for regression in engineering E. Cross T. Rogers D. J. Pitchforth S. Gibson Matthew R. Jones 54 9 0 19 Sep 2023
Gaussian process deconvolution Felipe A. Tobar Arnaud Robert Jorge F. Silva 67 5 0 08 May 2023
GaPT: Gaussian Process Toolkit for Online Regression with Application to Learning Quadrotor Dynamics Francesco Crocetti Jeffrey Mao Alessandro Saviolo G. Costante Giuseppe Loianno GP 52 6 0 14 Mar 2023
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting Yunyao Cheng Chenjuan Guo Kai Chen Kai Zhao B. Yang Jiandong Xie Christian S. Jensen Feiteng Huang Kai Zheng AI4TS 72 1 0 20 Dec 2022
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior Yohan Jung Jinkyoo Park BDL 58 0 0 22 Oct 2022
A Principled Method for the Creation of Synthetic Multi-fidelity Data Sets Clyde Fare Peter Fenner Edward O. Pyzer-Knapp 114 2 0 11 Aug 2022
Shallow and Deep Nonparametric Convolutions for Gaussian Processes Thomas M. McDonald M. Ross M. Smith Mauricio A. Alvarez 53 1 0 17 Jun 2022
Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains Haitao Liu Kai Wu Yew-Soon Ong Chao Bian Xiaomo Jiang Xiaofang Wang 55 8 0 25 Feb 2022
Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures Matias Altamirano Felipe A. Tobar 27 6 0 18 Feb 2022
Geometry-Aware Hierarchical Bayesian Learning on Manifolds Yonghui Fan Yalin Wang 33 2 0 30 Oct 2021
Multi-Task Neural Processes Donggyun Kim Seongwoong Cho Wonkwang Lee Seunghoon Hong 50 0 0 28 Oct 2021
Scalable Multi-Task Gaussian Processes with Neural Embedding of Coregionalization Haitao Liu Jiaqi Ding Xinyu Xie Xiaomo Jiang Yusong Zhao Xiaofang Wang BDL 50 17 0 20 Sep 2021
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition Shengyang Sun Jiaxin Shi A. Wilson Roger C. Grosse BDL 31 7 0 10 Jun 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 102 30 0 18 Mar 2021
The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain F. Simpson A. Boukouvalas Václav Cadek E. Sarkans N. Durrande 43 3 0 11 Mar 2021
Transferring model structure in Bayesian transfer learning for Gaussian process regression Milan Papez A. Quinn 41 12 0 18 Jan 2021
Cluster-Specific Predictions with Multi-Task Gaussian Processes Arthur Leroy Pierre Latouche Benjamin Guedj S. Gey 28 4 0 16 Nov 2020
Bayesian Reconstruction of Fourier Pairs Felipe A. Tobar Lerko Araya-Hernández P. Huijse Petar M. Djurić 43 5 0 09 Nov 2020
Approximate Inference for Spectral Mixture Kernel Yohan Jung Kyungwoo Song Jinkyoo Park BDL 20 2 0 12 Jun 2020
On Negative Transfer and Structure of Latent Functions in Multi-output Gaussian Processes Moyan Li Raed Al Kontar 47 7 0 06 Apr 2020
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes Seokhyun Chung Raed Al Kontar Zhenke Wu 30 5 0 19 Feb 2020
Gaussian process imputation of multiple financial series T. Wolff Alejandro Cuevas Felipe A. Tobar AI4TS 68 8 0 11 Feb 2020
MOGPTK: The Multi-Output Gaussian Process Toolkit T. Wolff Alejandro Cuevas Felipe A. Tobar GP 64 48 0 09 Feb 2020
Conditional Deep Gaussian Processes: multi-fidelity kernel learning Chi-Ken Lu Patrick Shafto 53 5 0 07 Feb 2020
The Wasserstein-Fourier Distance for Stationary Time Series Elsa Cazelles Arnaud Robert Felipe A. Tobar AI4TS 55 35 0 11 Dec 2019
A Fully Natural Gradient Scheme for Improving Inference of the Heterogeneous Multi-Output Gaussian Process Model Juan J. Giraldo Mauricio A. Alvarez BDL 98 5 0 22 Nov 2019
Band-Limited Gaussian Processes: The Sinc Kernel Felipe A. Tobar 45 20 0 16 Sep 2019
Latent Function Decomposition for Forecasting Li-ion Battery Cells Capacity: A Multi-Output Convolved Gaussian Process Approach Abdallah A. Chehade A. Hussein BDL 23 16 0 19 Jul 2019
Compositionally-Warped Gaussian Processes Gonzalo Rios Felipe A. Tobar 50 43 0 23 Jun 2019
Low-pass filtering as Bayesian inference Cristobal Valenzuela Felipe A. Tobar AI4TS 31 2 0 09 Feb 2019
NIPS - Not Even Wrong? A Systematic Review of Empirically Complete Demonstrations of Algorithmic Effectiveness in the Machine Learning and Artificial Intelligence Literature Franz J. Király Bilal A. Mateen R. Sonabend 95 10 0 18 Dec 2018
Bayesian Nonparametric Spectral Estimation Felipe A. Tobar 57 30 0 06 Sep 2018
Multi-Output Convolution Spectral Mixture for Gaussian Processes Kai Chen Twan van Laarhoven P. Groot Jinsong Chen E. Marchiori 82 11 0 07 Aug 2018
Multitask Gaussian Process with Hierarchical Latent Interactions Kai Chen Twan van Laarhoven E. Marchiori Feng Yin Shuguang Cui 84 6 0 03 Aug 2018
Heterogeneous Multi-output Gaussian Process Prediction P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 61 72 0 19 May 2018
Learning non-Gaussian Time Series using the Box-Cox Gaussian Process Gonzalo Rios Felipe A. Tobar GP 38 14 0 19 Mar 2018