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Based on direct integrals, a framework allowing to integrate a parametrised family of reproducing kernels with respect to some measure on the parameter space is developed. By pointwise integration, one obtains again a reproducing kernel…

Functional Analysis · Mathematics 2012-02-21 Thomas Hotz , Fabian J. E. Telschow

We consider two approaches for obtain of the generalized Ito-Wentzell formula: the first way uses the generalized Ito's formula; the second one is based on a concept of kernel functions for integral invariants.

Probability · Mathematics 2013-09-13 Valery Doobko , Elena Karachanskaya

We consider the algebra of mixed multidimensional integral operators. In particular, Fredholm integral operators of the first and second kind belongs to this algebra. For the piecewise constant kernels we provide an explicit representation…

Functional Analysis · Mathematics 2017-06-20 Anton A. Kutsenko

Implicit neural representations (INRs), which leverage neural networks to represent signals by mapping coordinates to their corresponding attributes, have garnered significant attention. They are extensively utilized for image…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Sheng Zheng , Chaoning Zhang , Dongshen Han , Fachrina Dewi Puspitasari , Xinhong Hao , Yang Yang , Heng Tao Shen

Kernel-based methods are heavily used in machine learning. However, they suffer from $O(N^2)$ complexity in the number $N$ of considered data points. In this paper, we propose an approximation procedure, which reduces this complexity to…

Numerical Analysis · Mathematics 2024-11-20 Johannes Hertrich

An integral representation of solutions of the wave equation as a superposition of other solutions of this equation is built. The solutions from a wide class can be used as building blocks for the representation. Considerations are based on…

Mathematical Physics · Physics 2015-05-13 M. V. Perel , M. S. Sidorenko

For a sequence of complex Wiener-Ito multiple integrals, the equivalence between the convergence of the symmetrized contraction norms and that of the non-symmetrized contraction norms is shown directly by means of a new version of complex…

Probability · Mathematics 2017-06-20 Yong Chen , Guo Jiang

We show that sampling or interpolation formulas in reproducing kernel Hilbert spaces can be obtained by reproducing kernels whose dual systems form molecules, ensuring that the size profile of a function is fully reflected by the size…

Functional Analysis · Mathematics 2022-05-04 José Luis Romero , Jordy Timo van Velthoven , Felix Voigtlaender

We prove that the formula which gives the Wiener chaos decomposition of the multiplication of two multiple Wiener integrals with symmetric kernels is a straightforward application of the Leibniz' formula.

Probability · Mathematics 2014-11-19 Ali Süleyman Üstünel

Fast Fourier transform algorithms are an arsenal of effective tools for solving various problems of analysis and high-speed processing of signals of various natures. Almost all of these algorithms are designed to process sequences of…

Data Structures and Algorithms · Computer Science 2025-04-11 Aleksandr Cariow

We construct, using the quantum dilogarithm, a series of *-representations of quantized cluster varieties. This includes a construction of infinite dimensional unitary projective representations of their discrete symmetry groups - the…

Quantum Algebra · Mathematics 2009-11-13 V. V. Fock , A. B. Goncharov

We provide a representation of the $C^*$-algebra generated by multidimensional integral operators with piecewise constant kernels and discrete ergodic operators. This representation allows us to find the spectrum and to construct the…

Mathematical Physics · Physics 2020-05-22 Anton A. Kutsenko

Let $Z^{\alpha,\beta}$ be the Rosenblatt sheet with the representation $$ Z^{\alpha,\beta}(t,s)=\int^t_0\int^s_0\int^t_0\int^s_0Q^\alpha(t,y_1,y_2)Q^\beta(s,u_1,u_2)B(dy_1,du_1)B(dy_2,du_2) $$ where $B$ is a Brownian sheet,…

Probability · Mathematics 2015-05-14 Guangjun Shen , Qian Yu

This study explores the utility of a kernel in complex Langevin simulations of quantum real-time dynamics on the Schwinger-Keldysh contour. We give several examples where we use a systematic scheme to find kernels that restore correct…

High Energy Physics - Lattice · Physics 2022-11-22 Daniel Alvestad , Rasmus Larsen , Alexander Rothkopf

In this paper, we characterize Probabilistic Principal Component Analysis in Hilbert spaces and demonstrate how the optimal solution admits a representation in dual space. This allows us to develop a generative framework for kernel methods.…

Machine Learning · Computer Science 2023-07-20 Henri De Plaen , Johan A. K. Suykens

This study explores the utility of a kernel in complex Langevin simulations of quantum real-time dynamics on the Schwinger-Keldysh contour. We give several examples where we use a systematic scheme to find kernels that restore correct…

High Energy Physics - Lattice · Physics 2022-12-16 Daniel Alvestad , Rasmus Larsen , Alexander Rothkopf

The Fourier transform and its inverse are well-known to have complex conjugate integral kernels. S.~Saitoh demonstrated that this relationship extends to the theory of integral transforms of Hilbert spaces of functions under certain…

Functional Analysis · Mathematics 2024-12-30 Akira Yamada

We construct a class of representations of the Heisenberg algebra in terms of the complex shift operators subject to the proper continuous limit imposed by the correspondence principle. We find a suitable Hilbert space formulation of our…

High Energy Physics - Theory · Physics 2007-05-23 Andrzej Z. Gorski , Jacek Szmigielski

Orthogonal polynomials of two real variables can often be represented in complex variables. We explore the connection between the two types of representations and study the structural relations of complex orthogonal polynomials. The complex…

Classical Analysis and ODEs · Mathematics 2013-07-31 Yuan Xu

Computational models are quantitative representations of systems. By analyzing and comparing the outputs of such models, it is possible to gain a better understanding of the system itself. Though as the complexity of model outputs…

Machine Learning · Computer Science 2022-12-13 Colin G. Cess , Stacey D. Finley
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