Mirage News

Marker-GMformer Predicts Lower Limb Biomechanics

The dynamic analysis of lower limb biomechanics is crucial for understanding gait, posture, and load distribution, which are foundational for ...

Wildfire prevention models miss key factor: How forests will change over decades

Eucalyptus trees, laden with flammable oils, could spread into Portugal's south-central region by 2060 if changing climate ...
IEEE

Multiscale Spatiotemporal Graph Convolutional Networks With Dynamic Delay Awareness for Traffic Forecasting

Abstract: The spatiotemporal dynamics of traffic forecasting make it a challenging task. In recent years, by adapting to the topology of traffic networks where road segments serve as nodes, graph ...
Frontiers

Exploring physical and functional EEG connectivity with multilayer graph transformer convolutional networks for emotion recognition

1 School of Automation, Nanjing University of Science and Technology, Nanjing, Jiangsu, China 2 School of Engineering, University of Birmingham, Birmingham, United Kingdom Electroencephalogram ...
IEEE

MBGCN: Multi-view Block-wise Graph Convolutional Networks on Large-scale Graphs

Abstract: Existing methods based on graph convolutional network often struggle with large-scale graphs due to their high computing consumption and inefficiency. Although strategies such as edge ...
Frontiers

DEG-BRIN-GCN: interpretable graph convolutional framework with differentially expressed genes brain region interaction network prior for AD diagnosis

Due to the intricate dynamic coupling between molecular networks and brain regions, early diagnosis and pathological mechanism analysis of Alzheimer's disease (AD) remain highly challenging. To ...
C&EN

GGCRB: A Graph Neural Network Approach for Predicting CircRNA–RBP Interactions Using Structural and Sequence Features

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The interaction between circular RNAs (circRNAs) and RNA-binding proteins (RBPs) plays ...
C&EN

Graph Convolutional Neural Network-Enabled Frontier Molecular Orbital Prediction: A Case Study with Neurotransmitters and Antidepressants

Department of Chemistry and Biochemistry, University of Wisconsin─Eau Claire, Eau Claire, Wisconsin 54702, United States ...
Scientific Research Publishing

Baldassarre, F. and Azizpour, H. (2019) Explainability Techniques for Graph Convolutional Networks. arXiv: 1905.13686.

ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...