Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem

16 November 2022

Papers citing "Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem"

23 / 23 papers shown

Title
Kernel-Based Optimal Control: An Infinitesimal Generator Approach Petar Bevanda Nicolas Hosichen Tobias Wittmann Jan Brüdigam Sandra Hirche Boris Houska 65 0 0 02 Dec 2024
Operator Learning Using Random Features: A Tool for Scientific Computing Nicholas H. Nelsen Andrew M. Stuart 32 12 0 12 Aug 2024
Optimal Estimation of Structured Covariance Operators Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 29 3 0 04 Aug 2024
Optimal Rates for Functional Linear Regression with General Regularization Naveen Gupta S. Sivananthan Bharath K. Sriperumbudur 21 4 0 14 Jun 2024
Covariance Operator Estimation via Adaptive Thresholding Omar Al Ghattas D. Sanz-Alonso 24 1 0 28 May 2024
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms D. Meunier Zikai Shen Mattes Mollenhauer Arthur Gretton Zhu Li 24 4 0 23 May 2024
Nonparametric Control Koopman Operators Petar Bevanda Bas Driessen Lucian-Cristian Iacob Roland Toth Stefan Sosnowski Sandra Hirche 26 2 0 12 May 2024
Operator Learning: Algorithms and Analysis Nikola B. Kovachki S. Lanthaler Andrew M. Stuart 36 22 0 24 Feb 2024
Optimal linear prediction with functional observations: Why you can use a simple post-dimension reduction estimator Won-Ki Seo 16 1 0 12 Jan 2024
A randomized algorithm to solve reduced rank operator regression G. Turri Vladimir Kostic P. Novelli Massimiliano Pontil 19 4 0 28 Dec 2023
Learned reconstruction methods for inverse problems: sample error estimates Luca Ratti 24 0 0 21 Dec 2023
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm Zhu Li D. Meunier Mattes Mollenhauer Arthur Gretton 21 5 0 12 Dec 2023
Inverse Problems with Learned Forward Operators Simon Arridge Andreas Hauptmann Yury Korolev 23 1 0 21 Nov 2023
On regularized polynomial functional regression Markus Holzleitner S. Pereverzyev 19 6 0 06 Nov 2023
Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters Omar Al Ghattas Jiaheng Chen D. Sanz-Alonso Nathan Waniorek 16 4 0 25 Oct 2023
Online Infinite-Dimensional Regression: Learning Linear Operators Vinod Raman Unique Subedi Ambuj Tewari 22 0 0 08 Sep 2023
Error Bounds for Learning with Vector-Valued Random Features S. Lanthaler Nicholas H. Nelsen 19 12 0 26 May 2023
Linear estimators for Gaussian random variables in Hilbert spaces Stefan Tappe 12 0 0 18 May 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 24 20 0 30 Mar 2023
Domain Generalization by Functional Regression Markus Holzleitner S. Pereverzyev Werner Zellinger OOD 21 4 0 09 Feb 2023
Nonparametric approximation of conditional expectation operators Mattes Mollenhauer P. Koltai 16 17 0 23 Dec 2020
A note on estimation in Hilbertian linear models Siegfried Hormann Łukasz Kidziński 61 34 0 14 Aug 2012
Conditional mean embeddings as regressors - supplementary Steffen Grunewalder Guy Lever Luca Baldassarre Sam Patterson A. Gretton Massimiliano Pontil 80 143 0 21 May 2012