This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses standard methods of interpolation.

Abstract. We introduce novel multiscale kernels using the random walk framework and derive corresponding embeddings and pairwise distances.

Multi-scale approaches ... For continuous signals, it holds that all scale-space kernels can be decomposed into the following sets of primitive smoothing kernels:.

Multiscale kernels are a new type of positive definite reproducing kernels in Hilbert spaces. They are constructed by a superposition of shifts and scales ...

A multi-task kernel K is the reproducing kernel of a Hilbert space of functions from an input space X which takes values in a Hilbert space Y . For example, in ...

Mar 20, 2016 · Abstract:Many real world graphs, such as the graphs of molecules, exhibit structure at multiple different scales, but most existing kernels ...

Abstract. This paper introduces a general principle for constructing multiscale kernels on surface meshes, and presents a construction of the multiscale ...

It takes into account structure in graphs at a range of different scales by building a hierarchy of nested subgraphs. These subgraphs are compared to each other ...

Request PDF | Multiscale kernels | This paper reconstructs multivariate functions from scattered data by a new multiscale technique.

Sep 11, 2022 · In this paper, a multiscale kernel-based residual convolutional neural network (CNN) algorithm is proposed for the diagnosis of ITSC faults. The ...