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2106.01121
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Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes
2 June 2021
Veit Wild
Motonobu Kanagawa
Dino Sejdinovic
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Papers citing
"Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes"
14 / 14 papers shown
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference
Neural Information Processing Systems (NeurIPS), 2024
Jonathan Wenger
Kaiwen Wu
Philipp Hennig
Jacob R. Gardner
Geoff Pleiss
John P. Cunningham
407
9
0
01 Nov 2024
Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
Nikola Pavlovic
Sudeep Salgia
Qing Zhao
243
0
0
20 Feb 2024
Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior
Neural Information Processing Systems (NeurIPS), 2023
Luke Travis
Kolyan Ray
486
5
0
29 Sep 2023
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
Neural Information Processing Systems (NeurIPS), 2023
J. Lin
Javier Antorán
Shreyas Padhy
David Janz
José Miguel Hernández-Lobato
Alexander Terenin
347
29
0
20 Jun 2023
Uncertainty quantification for sparse spectral variational approximations in Gaussian process regression
Electronic Journal of Statistics (EJS), 2022
D. Nieman
Botond Szabó
Harry Van Zanten
374
6
0
21 Dec 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning
Neural Information Processing Systems (NeurIPS), 2022
Zhijie Deng
Feng Zhou
Jun Zhu
BDL
247
29
0
23 Oct 2022
Log-Linear-Time Gaussian Processes Using Binary Tree Kernels
Neural Information Processing Systems (NeurIPS), 2022
Michael K. Cohen
Sam Daulton
Michael A. Osborne
GP
336
6
0
04 Oct 2022
Gaussian Process Koopman Mode Decomposition
Neural Computation (Neural Comput.), 2022
Takahiro Kawashima
H. Hino
188
8
0
09 Sep 2022
Collaborative Learning in Kernel-based Bandits for Distributed Users
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Sudeep Salgia
Sattar Vakili
Qing Zhao
FedML
291
7
0
16 Jul 2022
Posterior and Computational Uncertainty in Gaussian Processes
Neural Information Processing Systems (NeurIPS), 2022
Jonathan Wenger
Geoff Pleiss
Marvin Pfortner
Philipp Hennig
John P. Cunningham
628
23
0
30 May 2022
Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning
International Conference on Machine Learning (ICML), 2022
Sattar Vakili
Jonathan Scarlett
Da-shan Shiu
A. Bernacchia
397
22
0
08 Feb 2022
Variational Gaussian Processes: A Functional Analysis View
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Veit Wild
George Wynne
GP
234
5
0
25 Oct 2021
Kernel PCA with the Nyström method
Fredrik Hallgren
335
3
0
12 Sep 2021
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization
Marco Rando
Luigi Carratino
S. Villa
Lorenzo Rosasco
482
8
0
16 Jun 2021
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