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Causal survival embeddings: Non-parametric counterfactual inference under right-censoring. [PDF]

Stat Methods Med Res
García Meixide C, Matabuena M.
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Reproducing kernel Hilbert spaces

2011
Hinter der Konstruktion von Hilberträumen mit reproduzierendem Kern verbirgt sich eine Theorie von Bijektionen bzw. Transformationen, die einen positiv definiten Kern mit einem Hilbertraum von Funktionen verbindet. Das Ziel dieser Diplomarbeit ist es einen Überblick über die Theorie der Hilberträume mit reproduzierendem Kern und ihrer Anwendungen zu ...
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Causal Discovery via Reproducing Kernel Hilbert Space Embeddings

Neural Computation, 2014
Causal discovery via the asymmetry between the cause and the effect has proved to be a promising way to infer the causal direction from observations. The basic idea is to assume that the mechanism generating the cause distribution p(x) and that generating the conditional distribution p(y|x) correspond to two independent natural processes and thus p(x)
Chen, Z., Zhang, K., Chan, L., Schoelkopf, B.   +3 more
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Reproducing Kernel Hilbert Spaces

2022
Lucas Valentin Umann, Wolfgang Karl Härdle   +1 more
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On Reproducing Kernel Hilbert Spaces of Polynomials

Mathematische Nachrichten, 1997
AbstractCertain Hilbert spaces of polynomials, called Szegö spaces [11], are studied. A transformation, called Hilbert traneformation, is constructed for every polynomial associatted with a Szegö space. An orthogonal set is found in a Szegö space which determines the norm of the space. A matrix factorization theory is obtained for defining polynomials.
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Pasting Reproducing Kernel Hilbert Spaces

2017
The aim of this article is to find the necessary and sufficient condition for the mapping $$\displaystyle{H_{K}(E) \ni f\mapsto (\,f\vert E_{1},f\vert E_{2}) \in H_{K\vert E_{1}\times E_{2}}(E_{1}) \oplus H_{K\vert E_{2}\times E_{2}}(E_{2})}$$ to be isomorphic, where K is a positive definite function on E = E1 + E2.
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Reproducing Kernel Hilbert Spaces and Discrimination

2015
In this chapter, it is examined to what extent RKHS’s allow one to discriminate between probability laws, that is determine their equivalence or singularity.
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