Fetching the paper…
Reading the bibliography…
In this article, we investigate the problem of estimating a spatially inhomogeneous function and its derivatives in the white noise model using Besov-Laplace priors.
Random tree Besov priors—towards fractal imaging
H. Kekkonen, M. Lassas, E. Saksman, and S. Siltanen · 1930
Earlier work this paper cites.
Nonlinear total variation based noise removal algorithms
L. I. Rudin, S. Osher, and E. Fatemi · 1991
Earlier work this paper cites.
Minimax estimation via wavelet shrinkage
D. L. Donoho and I. M. Johnstone · 1998
Earlier work this paper cites.
Wavelets, approximation, and statistical applications , volume 129 of Lecture Notes in Statistics
W. Härdle, G. Kerkyacharian, D. Picard, and A. Tsybakov · 1998
Earlier work this paper cites.
Convergence rates of posterior distributions
S. Ghosal, J. K. Ghosh, and A. W. van der Vaart · 2000
Earlier work this paper cites.
Rates of convergence of posterior distributions
X. Shen and L. Wasserman · 2001
Earlier work this paper cites.
Asymptotic equivalence theory for nonparametric regression with random design
L. D. Brown, T. T. Cai, M. G. Low, and C.-H. Zhang · 2002
Earlier work this paper cites.
Can one use total variation prior for edge-preserving Bayesian inversion?
M. Lassas and S. Siltanen · 2004
Earlier work this paper cites.
Introduction to nonparametric estimation
A. B. Tsybakov · 2004
Earlier work this paper cites.
Bayesian wavelet-based image deconvolution: a GEM algorithm exploiting a class of heavy-tailed priors
J. M. Bioucas-Dias · 2005
Earlier work this paper cites.
Wavelet-based reconstruction for limited-angle x-ray tomography
M. Rantala, S. Vänskä, S. Järvenpää, M. Kalke, M. Lassas, J. Moberg, and S. Siltanen · 2005
Earlier work this paper cites.
Asymptotic approximations for probability integrals
K. W. Breitung · 2006
Earlier work this paper cites.
Convergence rates of posterior distributions for non-i.i.d. observations
S. Ghosal and A. van der Vaart · 2007
Earlier work this paper cites.
On universal bayesian adaptation
J. Lember and A. van der Vaart · 2007
Earlier work this paper cites.
Bayesian multiresolution method for local tomography in dental x-ray imaging
K. Niinimäki, S. Siltanen, and V. Kolehmainen · 2007
Earlier work this paper cites.
Gradient flows: in metric spaces and in the space of probability measures
L. Ambrosio, N. Gigli, and G. Savaré · 2008
Earlier work this paper cites.
Asymptotic equivalence for nonparametric regression with multivariate and random design
M. Reiß · 2008
Earlier work this paper cites.
Rates of contraction of posterior distributions based on Gaussian process priors
A. W. van der Vaart and J. H. van Zanten · 2008
Earlier work this paper cites.
Discretization-invariant Bayesian inversion and Besov space priors
M. Lassas, E. Saksman, and S. Siltanen · 2009
Earlier work this paper cites.
Adaptive Bayesian estimation using a Gaussian random field with inverse gamma bandwidth
A. W. van der Vaart and J. H. van Zanten · 2009
Cited alongside, same era.
Statistical X-ray tomography using empirical Besov priors
S. Vänskä, M. Lassas, and S. Siltanen · 2009
Cited alongside, same era.
NIST handbook of mathematical functions
F. W. Olver, D. W. Lozier, R. F. Boisvert, and C. W. Clark · 2010
Cited alongside, same era.
Inverse problems: a Bayesian perspective
A. M. Stuart · 2010
Cited alongside, same era.
Rates of contraction for posterior distributions in L r L^{r} -metrics, 1 ≤ r ≤ ∞ 1\leq r\leq\infty
E. Giné and R. Nickl · 2011
Cited alongside, same era.
Besov priors for Bayesian inverse problems
M. Dashti, S. Harris, and A. M. Stuart · 2012
Sparsity-promoting and edge-preserving maximum a posteriori
S. Agapiou, M. Burger, M. Dashti, and T. Helin · 2018
Later among the works it cites.
Functional inequalities for Gaussian convolutions of compactly supported measures: Explicit bounds and dimension dependence
J.-B. Bardet, N. Gozlan, F. Malrieu, and P.-A. Zitt · 2018
Later among the works it cites.
Dimension-robust mcmc in bayesian inverse problems
V. Chen, M. M. Dunlop, O. Papaspiliopoulos, and A. M. Stuart · 2018
Later among the works it cites.
Statistical aspects of wasserstein distances
V. M. Panaretos and Y. Zemel · 2019
Later among the works it cites.
On uniform continuity of posterior distributions
E. Dolera and E. Mainini · 2020
Later among the works it cites.
Sobolev norm learning rates for regularized least-squares algorithms
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Sparsity-promoting Bayesian inversion
V. Kolehmainen, M. Lassas, K. Niinimäki, and S. Siltanen · 2012
Cited alongside, same era.
Interpolation of spatial data: some theory for kriging
M. L. Stein · 2012
Cited alongside, same era.
Bayesian optimal adaptive estimation using a sieve prior
J. Arbel, G. Gayraud, and J. Rousseau · 2013
Cited alongside, same era.
Gaussian process modeling of derivative curves
T. Holsclaw, B. Sansó, H. K. Lee, K. Heitmann, S. Habib, D. Higdon, and U. Alam · 2013
Cited alongside, same era.
Bayesian inverse problems with non-conjugate priors
K. Ray · 2013
Cited alongside, same era.
On the Bernstein–von Mises phenomenon for nonparametric Bayes procedures
I. Castillo and R. Nickl · 2014
Cited alongside, same era.
S. Fischer and I. Steinwart · 2020
Later among the works it cites.
Rates of contraction of posterior distributions based on p-exponential priors
S. Agapiou, M. Dashti, and T. Helin · 2021
Later among the works it cites.
Functional inequalities for perturbed measures with applications to log-concave measures and to some bayesian problems
P. Cattiaux and A. Guillin · 2022
Later among the works it cites.
Nonparametric Bayesian inference for reversible multidimensional diffusions
M. Giordano and K. Ray · 2022
Later among the works it cites.
On the inability of gaussian process regression to optimally learn compositional functions
M. Giordano, K. Ray, and J. Schmidt-Hieber · 2022
Later among the works it cites.
Optimal plug-in gaussian processes for modelling derivatives
Z. Liu and M. Li · 2022
Later among the works it cites.
Deep gaussian process priors for bayesian inference in nonlinear inverse problems
K. Abraham and N. Deo · 2023
Later among the works it cites.
Lipschitz continuity of probability kernels in the optimal transport framework
E. Dolera and E. Mainini · 2023
Later among the works it cites.
Besov-Laplace priors in density estimation: optimal posterior contraction rates and adaptation
M. Giordano · 2023
Later among the works it cites.
Heavy-tailed bayesian nonparametric adaptation
S. Agapiou and I. Castillo · 2024
Closest in time.
Adaptive inference over besov spaces in the white noise model using p-exponential priors
S. Agapiou and A. Savva · 2024
Closest in time.
Laplace priors and spatial inhomogeneity in bayesian inverse problems
S. Agapiou and S. Wang · 2024
Closest in time.
Strong posterior contraction rates via wasserstein dynamics
E. Dolera, S. Favaro, and E. Mainini · 2024
Closest in time.