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Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation
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Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation

Yifan Chen
H. Owhadi
Andrew M. Stuart
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Papers citing "Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation"

15 / 15 papers shown
Title
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features
Oliver R. A. Dunbar
Nicholas H. Nelsen
Maya Mutic
129
7
0
30 Jun 2024
Learning dynamical systems from data: a simple cross-validation perspective
Learning dynamical systems from data: a simple cross-validation perspective
B. Hamzi
H. Owhadi
66
41
0
09 Jul 2020
Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows
Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows
G. Yoo
H. Owhadi
67
21
0
19 Feb 2020
Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems
Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems
A. Teckentrup
60
67
0
31 Aug 2019
Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency
Hyperparameter Estimation in Bayesian MAP Estimation: Parameterizations and Consistency
Matthew M. Dunlop
T. Helin
Andrew M. Stuart
64
18
0
10 May 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
Jaehoon Lee
Lechao Xiao
S. Schoenholz
Yasaman Bahri
Roman Novak
Jascha Narain Sohl-Dickstein
Jeffrey Pennington
213
1,110
0
18 Feb 2019
Kernel Flows: from learning kernels from data into the abyss
Kernel Flows: from learning kernels from data into the abyss
H. Owhadi
G. Yoo
88
90
0
13 Aug 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot
Franck Gabriel
Clément Hongler
275
3,223
0
20 Jun 2018
Cross-validation estimation of covariance parameters under fixed-domain asymptotics
Cross-validation estimation of covariance parameters under fixed-domain asymptotics
François Bachoc
A. Lagnoux
Thi Mong Ngoc Nguyen
65
22
0
10 Oct 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,510
0
10 Dec 2015
Deep Kernel Learning
Deep Kernel Learning
A. Wilson
Zhiting Hu
Ruslan Salakhutdinov
Eric Xing
BDL
256
889
0
06 Nov 2015
Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification
Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification
François Bachoc
114
228
0
18 Jan 2013
Bayes procedures for adaptive inference in inverse problems for the white noise model
Bayes procedures for adaptive inference in inverse problems for the white noise model
B. Knapik
Botond Szabó
A. van der Vaart
J. H. Zanten
71
81
0
17 Sep 2012
Bayesian inverse problems with Gaussian priors
Bayesian inverse problems with Gaussian priors
B. Knapik
A. van der Vaart
J. H. Zanten
114
228
0
14 Mar 2011
Consistency of cross validation for comparing regression procedures
Consistency of cross validation for comparing regression procedures
Yuhong Yang
182
178
0
20 Mar 2008