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 ...
MicroRNAs (miRNAs) are of significance in tuning and buffering gene expression. Despite abundant analysis tools that have been developed in the last two decades, plant miRNA identification from ...
Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit ...
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 ...
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 ...
Hematoma volume (HV) is a significant diagnosis for determining the clinical stage and therapeutic approach for intracerebral hemorrhage (ICH). The aim of this study is to develop a robust deep ...
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 ...
Accurate inference of gene interactions and causality is required for pathway reconstruction, which remains a major goal for many studies. Here, we take advantage of 2 recent technological ...
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