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Cited article:
Houman Owhadi , Clint Scovel
ESAIM: PS, 21 (2017) 251-274
Published online: 2017-12-12
This article has been cited by the following article(s):
9 articles
DECISION THEORETIC BOOTSTRAPPING
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Do ideas have shape? Idea registration as the continuous limit of artificial neural networks
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Generalized Bayes approach to inverse problems with model misspecification
Youngsoo Baek, Wilkins Aquino and Sayan Mukherjee Inverse Problems 39 (10) 105011 (2023) https://doi.org/10.1088/1361-6420/acf51c
Uncertainty quantification of the 4th kind; optimal posterior accuracy-uncertainty tradeoff with the minimum enclosing ball
Hamed Hamze Bajgiran, Pau Batlle, Houman Owhadi, et al. Journal of Computational Physics 471 111608 (2022) https://doi.org/10.1016/j.jcp.2022.111608
GAN-Based Priors for Quantifying Uncertainty in Supervised Learning
Dhruv V. Patel and Assad A. Oberai SIAM/ASA Journal on Uncertainty Quantification 9 (3) 1314 (2021) https://doi.org/10.1137/20M1354210
Learning dynamical systems from data: A simple cross-validation perspective, part I: Parametric kernel flows
Boumediene Hamzi and Houman Owhadi Physica D: Nonlinear Phenomena 421 132817 (2021) https://doi.org/10.1016/j.physd.2020.132817
Kernel Flows: From learning kernels from data into the abyss
Houman Owhadi and Gene Ryan Yoo Journal of Computational Physics 389 22 (2019) https://doi.org/10.1016/j.jcp.2019.03.040
Random Forward Models and Log-Likelihoods in Bayesian Inverse Problems
H. C. Lie, T. J. Sullivan and A. L. Teckentrup SIAM/ASA Journal on Uncertainty Quantification 6 (4) 1600 (2018) https://doi.org/10.1137/18M1166523
Gaussian approximation of general non-parametric posterior distributions
Guang Cheng and Zuofeng Shang Information and Inference: A Journal of the IMA 7 (3) 509 (2018) https://doi.org/10.1093/imaiai/iax017