Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

Abstract: In skeleton-based human action recognition domain, the methods based on graph convolution networks have great success recently. However, most graphical neural networks consider the skeleton ...

An intensive, fast-paced summer school for predoctoral students to build mathematical intuitions and skills necessary to enter the fields of theoretical neuroscience and foundational machine learning ...

Get to grips with impulse responses and convolution reverb in our guide to one of Logic's most versatile reverb plugins When you purchase through links on our site, we may earn an affiliate commission ...

Spinal cord injury (SCI) may lead to impaired motor function, autonomic nervous system dysfunction, and other dysfunctions. Brain-computer Interface (BCI) system based on motor imagery (MI) can ...

The use of an artificial intelligence (AI)-based prediction model of the structure-odor relationship (SOR) has shown great potential in the replacement of human panelists in gas ...

This exploration aims to study the emotion recognition of speech and graphic visualization of expressions of learners under the intelligent learning environment of the Internet. After comparing the ...

J Clin Pharmacol. 2021 Aug; 61(8): 1081–1095. The availability of a model describing the time course of drug concentration profile is instrumental for implementing such a pharmacometric framework. The ...

Abstract: Graph classification is a fundamental but challenging issue for numerous real-world applications. Despite recent great progress in image/video classification, convolutional neural networks ...

The dramatic success in machine learning has led to an explosion of artificial intelligence (AI) applications and increasing expectations for autonomous systems that exhibit human-level intelligence.