Single neurons in mouse sensorimotor cortex are organized by their activity features into distinct subpopulations with area-spanning footprints whose boundaries align closely with anatomical and ...

The Layer-wise Relevance Propagation (LRP) algorithm explains a classifer's prediction specific to a given data point by attributing relevance scores to important components of the input by using the ...

MATLAB (short for Matrix Laboratory) is a powerful software tool used for technical computing and visualization. It is widely used in a variety of fields, including engineering, science, finance, and ...

Abstract: This paper describes a predictive model using MATLAB machine learning tools for nonlinear regression, support vector machine and neural network. Data center performance measures such as run ...

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

A neural network was trained to accurately predict the entire single-event specific energy spectra for use in alpha-particle microdosimetry calculations. Microdosimetry considers the stochastic nature ...

Abstract: In the last few years, the increasing development of various tools to make fake videos from real videos has been raised. Thus, several models/approaches have been constructed to detect and ...

Laboratory of Data Science and Digital Inclusion, Institut de Mathématiques et de Sciences Physiques, Université d’Abomey-Calavi, Abomey-Calavi, Bénin. Diabetes is a chronic disease. In 2019, it was ...

TensorFlow is an open-source framework developed by Google scientists and engineers for numerical computing. TensorFlow.NET is a library that provides a .NET Standard binding for TensorFlow, allowing ...

We demonstrate that a neural network automatically solves, explains, and generates university-level problems from the largest Massachusetts Institute of Technology (MIT) mathematics courses at a human ...