Scaling up the Automatic Statistician: Scalable Structure Discovery
using Gaussian Processes

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Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes

8 June 2017

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Papers citing "Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes"

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Title
Trace Encoding in Process Mining: a survey and benchmarking Sylvio Barbon Junior Paolo Ceravolo R. Oyamada G. Tavares AI4TS 75 21 0 05 Jan 2023
Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence Stefan Blücher Klaus-Robert Muller Stefan Chmiela 79 4 0 24 Dec 2022
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
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations Andreas Besginow Markus Lange-Hegermann 78 11 0 26 Aug 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 125 78 0 28 May 2022
Surrogate modeling for Bayesian optimization beyond a single Gaussian process Qin Lu Konstantinos D. Polyzos Bingcong Li G. Giannakis GP 62 23 0 27 May 2022
Adaptive Cholesky Gaussian Processes Simon Bartels Kristoffer Stensbo-Smidt Pablo Moreno-Muñoz Wouter Boomsma J. Frellsen Søren Hauberg 78 3 0 22 Feb 2022
Incremental Ensemble Gaussian Processes Qin Lu G. V. Karanikolas G. Giannakis 97 25 0 13 Oct 2021
Online structural kernel selection for mobile health Eura Shin Pedja Klasnja Susan Murphy Finale Doshi-Velez 39 1 0 21 Jul 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 137 133 0 14 May 2021
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients A. Artemev David R. Burt Mark van der Wilk 77 19 0 16 Feb 2021
Time series forecasting with Gaussian Processes needs priors Giorgio Corani A. Benavoli Marco Zaffalon GP AI4TS 59 29 0 17 Sep 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression David R. Burt C. Rasmussen Mark van der Wilk 82 74 0 01 Aug 2020
Large Scale Tensor Regression using Kernels and Variational Inference Robert Hu Geoff K. Nicholls Dino Sejdinovic 37 4 0 11 Feb 2020
Learning Invariances using the Marginal Likelihood Mark van der Wilk Matthias Bauer S. T. John J. Hensman 92 86 0 16 Aug 2018
Automatic Bayesian Density Analysis Antonio Vergari Alejandro Molina Robert Peharz Zoubin Ghahramani Kristian Kersting Isabel Valera 41 35 0 24 Jul 2018