Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Michael Kupper"'
Publikováno v:
PLoS ONE, Vol 5, Iss 12, p e16000 (2010)
The CCN family of proteins, especially its prominent member, the Connective tissue growth factor (CTGF/CCN2) has been identified as a possible biomarker for the diagnosis of fibrotic diseases. As a downstream mediator of TGF-β1 signalling, it is inv
Externí odkaz:
https://doaj.org/article/fb6015fabc9143cd99a3748038213ff6
We study the existence of minimal supersolutions of BSDEs under a family of mutually singular probability measures. We consider generators that are jointly lower semicontinuous, positive, and either convex in the control variable and monotone in the
Externí odkaz:
http://arxiv.org/abs/1306.6545
Autor:
Jonas Blessing, Michael Kupper
Publikováno v:
Journal de Mathématiques Pures et Appliquées. 163:654-672
Publikováno v:
Journal of Evolution Equations. 21:2491-2521
In this paper, we investigate convex semigroups on Banach lattices with order continuous norm, having $L^p$-spaces in mind as a typical application. We show that the basic results from linear $C_0$-semigroup theory extend to the convex case. We prove
Publikováno v:
Studia Mathematica. 260:121-140
We derive two types of representation results for increasing convex functionals in terms of countably additive measures. The first is a max-representation of functionals defined on spaces of real-valued continuous functions and the second a sup-repre
Autor:
Jonas Blessing, Michael Kupper
Publikováno v:
Potential Analysis.
Under suitable conditions on a family (I(t))t≥ 0of Lipschitz mappings on a complete metric space, we show that, up to a subsequence, the strong limit$S(t):=\lim _{n\to \infty }(I(t 2^{-n}))^{2^{n}}$S(t):=limn→∞(I(t2−n))2nexists for all dyadic
Autor:
Michael Kupper, José M. Zapata
Publikováno v:
Fuzzy Sets and Systems. :108506
Autor:
Stephan Eckstein, Michael Kupper
Publikováno v:
Applied Mathematics & Optimization. 83:639-667
This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it to a fini
We consider a nonlinear random walk which, in each time step, is free to choose its own transition probability within a neighborhood (w.r.t. Wasserstein distance) of the transition probability of a fixed L\'evy process. In analogy to the classical fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::54c89285365b4862936ae65a866ee9f2
https://hdl.handle.net/11353/10.1604322
https://hdl.handle.net/11353/10.1604322
In this paper, we present a duality theory for the robust utility maximisation problem in continuous time for utility functions defined on the positive real line. Our results are inspired by – and can be seen as the robust analogues of – the semi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a014c23c10c85e373c74425ec53d23a