Dual Graph Convolutional Network for Hyperspectral Images With Spatial Graph and Spectral Multigraph
Abstract: To accurately represent the graph structure of the pixel nodes in the hyperspectral remote sensing image classification based on graph convolutional networks (GCNs), a spectral multigraph ...
Abstract: Prediction of the next event is important for organizations to improve and optimize their system process to achieve organizational goals. Existing predictive models are limited since they ...
An R package for using discrete Morse theory to analyze a data set using the Mapper algorithm described in: G. Singh, F. Memoli, G. Carlsson (2007). Topological Methods for the Analysis of High ...
The same family of artificial intelligence that powers today's image generators is now being aimed at one of biology's ...
Learn how to use the Relative Vigor Index (RVI) to measure trend strength and smooth price fluctuations in trading, with an ...
Heterogeneous Graph Transformer is a graph neural network architecture that can deal with large-scale heterogeneous and dynamic graphs. You can see our WWW 2020 paper “Heterogeneous Graph Transformer” ...
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