High-throughput omics datasets provide detailed snapshots of the cellular transcriptome, but their destructive nature prevents tracking the time evolution of a cell’s molecular state. This limitation, ...

Introduced is the notion of minimality for spectral representations of sum- and max-infinitely divisible processes and it is shown that the minimal spectral representation on a Borel space exists and ...

Abstract: Large-scale classification is an important task of machine learning, especially in the smart city field, which is a big data environment. In recent years, single-threaded optimization ...

This repository contains the PyTorch implementation for “Intelligent Fault Classification Exploration Inspired by Suprathreshold Stochastic Resonance”. The proposed activation function can be used by ...

Abstract: Convolutional neural networks (CNNs) have shown impressive performance in hyperspectral image (HSI) classification. However, these deep learning methods still face two major challenges. One ...

This is a preview. Log in through your library . Abstract In this paper we discuss a counter system whose output is a stochastic point process such that the time intervals between pairs of successive ...

Any process which may be described in terms of probabilities. In such a process, although the details of individual events are unpredictable, the overall character or behaviour of the system will be.

In extreme ultraviolet (EUV) lithography, stochastics are events that have random variables. These variations, called stochastic effects, sometimes cause unwanted defects and pattern roughness in ...