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Statistical inverse learning problems with random observations

Statistical inverse learning problems with random observations

23 December 2023
Abhishake
T. Helin
Nicole Mucke
ArXiv (abs)PDFHTML

Papers citing "Statistical inverse learning problems with random observations"

21 / 21 papers shown
Title
On Learning the Optimal Regularization Parameter in Inverse Problems
On Learning the Optimal Regularization Parameter in Inverse Problems
Jonathan Chirinos-Rodriguez
Ernesto De Vito
C. Molinari
Lorenzo Rosasco
S. Villa
210
3
0
27 Nov 2023
Least squares approximations in linear statistical inverse learning
  problems
Least squares approximations in linear statistical inverse learning problems
T. Helin
35
2
0
22 Nov 2022
Statistical Inverse Problems in Hilbert Scales
Statistical Inverse Problems in Hilbert Scales
Abhishake Rastogi
20
3
0
28 Aug 2022
Learning the optimal Tikhonov regularizer for inverse problems
Learning the optimal Tikhonov regularizer for inverse problems
Giovanni S. Alberti
Ernesto De Vito
Matti Lassas
Luca Ratti
Matteo Santacesaria
61
30
0
11 Jun 2021
Designing truncated priors for direct and inverse Bayesian problems
Designing truncated priors for direct and inverse Bayesian problems
S. Agapiou
Peter Mathé
25
5
0
21 May 2021
Convex regularization in statistical inverse learning problems
Convex regularization in statistical inverse learning problems
T. Bubba
Martin Burger
T. Helin
Luca Ratti
52
9
0
18 Feb 2021
Stochastic Gradient Descent in Hilbert Scales: Smoothness,
  Preconditioning and Earlier Stopping
Stochastic Gradient Descent in Hilbert Scales: Smoothness, Preconditioning and Earlier Stopping
Nicole Mücke
Enrico Reiss
37
7
0
18 Jun 2020
Inverse learning in Hilbert scales
Inverse learning in Hilbert scales
Abhishake Rastogi
Peter Mathé
10
6
0
24 Feb 2020
Tikhonov regularization with oversmoothing penalty for nonlinear
  statistical inverse problems
Tikhonov regularization with oversmoothing penalty for nonlinear statistical inverse problems
Abhishake Rastogi
53
5
0
01 Feb 2020
Consistency of Bayesian inference with Gaussian process priors in an
  elliptic inverse problem
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
M. Giordano
Richard Nickl
96
62
0
16 Oct 2019
Smoothed residual stopping for statistical inverse problems via
  truncated SVD estimation
Smoothed residual stopping for statistical inverse problems via truncated SVD estimation
Bernhard Stankewitz
33
9
0
30 Sep 2019
Lepskii Principle in Supervised Learning
Lepskii Principle in Supervised Learning
Gilles Blanchard
Peter Mathé
Nicole Mücke
55
12
0
26 May 2019
Consistent Inversion of Noisy Non-Abelian X-Ray Transforms
Consistent Inversion of Noisy Non-Abelian X-Ray Transforms
F. Monard
Richard Nickl
G. Paternain
43
58
0
02 May 2019
Convergence analysis of Tikhonov regularization for non-linear
  statistical inverse learning problems
Convergence analysis of Tikhonov regularization for non-linear statistical inverse learning problems
Abhishake Rastogi
Gilles Blanchard
Peter Mathé
28
8
0
14 Feb 2019
Convergence rates for Penalised Least Squares Estimators in
  PDE-constrained regression problems
Convergence rates for Penalised Least Squares Estimators in PDE-constrained regression problems
Richard Nickl
Sara van de Geer
Sven Wang
72
61
0
24 Sep 2018
Bayesian linear inverse problems in regularity scales
Bayesian linear inverse problems in regularity scales
S. Gugushvili
A. van der Vaart
D. Yan
40
18
0
25 Feb 2018
Early stopping for statistical inverse problems via truncated SVD
  estimation
Early stopping for statistical inverse problems via truncated SVD estimation
Gilles Blanchard
M. Hoffmann
M. Reiß
49
21
0
19 Oct 2017
Optimal adaptation for early stopping in statistical inverse problems
Optimal adaptation for early stopping in statistical inverse problems
Gilles Blanchard
M. Hoffmann
M. Reiß
42
35
0
24 Jun 2016
Optimal Rates For Regularization Of Statistical Inverse Learning
  Problems
Optimal Rates For Regularization Of Statistical Inverse Learning Problems
Gilles Blanchard
Nicole Mücke
476
143
0
14 Apr 2016
Large Noise in Variational Regularization
Large Noise in Variational Regularization
Martin Burger
T. Helin
Hanne Kekkonen
101
15
0
01 Feb 2016
Regularization in kernel learning
Regularization in kernel learning
S. Mendelson
Joe Neeman
350
145
0
13 Jan 2010
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