In the last few years, there have been several revolutions in the field of deep learning,
mainly headlined by the large impact of Generative Adversarial Networks (GANs). GANs not …

This article presents a new convolutional neural network (CNN) topology using wavelet
kernels to detect and discriminate single or multiple partial discharge (PD) locations in high …

Natural gas is playing a key role in the Carbon Neutral path, which is clean and abundant.
However it is difficult to collect sufficient data of urban natural gas consumption in China …

This article addresses the issue of representing electroencephalographic (EEG) signals in
an efficient way. While classical approaches use a fixed Gabor dictionary to analyze EEG …

We present a novel kernel regression framework for smoothing scalar surface data using the
Laplace–Beltrami eigenfunctions. Starting with the heat kernel constructed from the …

This tutorial reference serves as a coherent overview of various statistical and mathematical
approaches used in brain network analysis, where modeling the complex structures and …

Metric learning has been shown to be highly effective to improve the performance of nearest
neighbor classification. In this paper, we address the problem of metric learning for …

Chemoinformatics is a research field concerned with the study of physical or biological
molecular properties through computer science׳ s research fields such as machine learning …

We present the discrete version of heat kernel smoothing on graph data structure. The
method is used to smooth data in an irregularly shaped domains in 3D images. New …

Challenge IEEE-ISBI/TCB : arxiv:1410.2663v1 [cs.CV] 10 Oct 2014 Page 1 Challenge IEEE-ISBI/TCB
: Application of Covariance matrices and wavelet marginals Florian Yger Tokyo Institute of …