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Ilja Klebanov
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A rigorous theory of conditional mean embeddings
I Klebanov, I Schuster, TJ Sullivan
SIAM Journal on Mathematics of Data Science 2 (3), 583-606, 2020
172020
Markov chain importance sampling—a highly efficient estimator for MCMC
I Schuster, I Klebanov
Journal of Computational and Graphical Statistics 30 (2), 260-268, 2020
102020
Axiomatic approach to variable kernel density estimation
I Klebanov
arXiv preprint arXiv:1805.01729, 2018
72018
The linear conditional expectation in Hilbert space
I Klebanov, B Sprungk, TJ Sullivan
Bernoulli 27 (4), 2267-2299, 2021
62021
-convergence of Onsager–Machlup functionals: I. With applications to maximum a posteriori estimation in Bayesian inverse problems
B Ayanbayev, I Klebanov, HC Lie, TJ Sullivan
Inverse Problems 38 (2), 025005, 2021
42021
Γ-convergence of Onsager–Machlup functionals: II. Infinite product measures on Banach spaces
B Ayanbayev, I Klebanov, HC Lie, TJ Sullivan
Inverse Problems 38 (2), 025006, 2021
42021
Objective priors in the empirical Bayes framework
I Klebanov, A Sikorski, C Schütte, S Röblitz
Scandinavian Journal of Statistics 48 (4), 1212-1233, 2021
22021
\Gamma-convergence of Onsager-Machlup functionals. Part I: With applications to maximum a posteriori estimation in Bayesian inverse problems
B Ayanbayev, I Klebanov, HC Lie, TJ Sullivan
arXiv preprint arXiv:2108.04597, 2021
22021
Γ-convergence of Onsager–Machlup functionals
B Ayanbayev, I Klebanov, HC Lie, TJ Sullivan
Part I: With applications to maximum a posteriori estimation in Bayesian …, 2021
22021
Approximation of PDEs with underlying continuity equations
I Klebanov
Technische Universität München, 2016
22016
Maximum a posteriori estimators in are well-defined for diagonal Gaussian priors
I Klebanov, P Wacker
arXiv preprint arXiv:2207.00640, 2022
12022
Adaptive convolutions
I Klebanov
arXiv preprint arXiv:1805.00703, 2018
12018
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Articles 1–12