Results 1 to 10 of about 37,604 (258)
Casting a graph net to catch dark showers
Strongly interacting dark sectors predict novel LHC signatures such as semi-visible jets resulting from dark showers that contain both stable and unstable dark mesons.
Elias Bernreuther, Thorben Finke, Felix Kahlhoefer, Michael Krämer, Alexander Mück
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Anomaly detection with convolutional Graph Neural Networks
We devise an autoencoder based strategy to facilitate anomaly detection for boosted jets, employing Graph Neural Networks (GNNs) to do so. To overcome known limitations of GNN autoencoders, we design a symmetric decoder capable of simultaneously ...
Oliver Atkinson +4 more
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Affinity-Point Graph Convolutional Network for 3D Point Cloud Analysis
Efficient learning of 3D shape representation from point cloud is one of the biggest requirements in 3D computer vision. In recent years, convolutional neural networks have achieved great success in 2D image representation learning.
Yang Wang, Shunping Xiao
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In this study, we adapt three spatial-temporal graph neural network models to the unique characteristics of crude oil, gold, and silver markets for forecasting purposes.
Parisa Foroutan, Salim Lahmiri
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A Review of Graph Neural Networks and Their Applications in Power Systems
Deep neural networks have revolutionized many machine learning tasks in power systems, ranging from pattern recognition to signal processing. The data in these tasks are typically represented in Euclidean domains.
Wenlong Liao +4 more
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Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model
Walking is an exercise that uses muscles and joints of the human body and is essential for understanding body condition. Analyzing body movements through gait has been studied and applied in human identification, sports science, and medicine.
Jungi Kim +3 more
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AAGCN: a graph convolutional neural network with adaptive feature and topology learning
In recent years, there has been a growing prevalence of deep learning in various domains, owing to advancements in information technology and computing power.
Bin Wang +3 more
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A Survey on Graph Neural Networks for Microservice-Based Cloud Applications
Graph neural networks (GNNs) have achieved great success in many research areas ranging from traffic to computer vision. With increased interest in cloud-native applications, GNNs are increasingly being investigated to address various challenges in ...
Hoa Xuan Nguyen +2 more
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Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network
In recent years, neural network algorithms have demonstrated tremendous potential for modulation classification. Deep learning methods typically take raw signals or convert signals into time–frequency images as inputs to convolutional neural networks ...
Dong Wang +4 more
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Introduction. PIWI-interacting RNAs are small and non-coding RNAs involved in gene regulation and transposable element repression, emerging as critical biomarkers and therapeutic targets in oncology. Advances in artificial intelligence, such as recurrent
Jheremy Sebastián Reyes +6 more
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