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 ...
We address the task of Probabilistic 3D Human Motion Prediction: from the past, predict the future. Here is an example from AMASS: Together with the latent diffusion model SkeletonDiffusion, we ...
Learn how to use the Relative Vigor Index (RVI) to measure trend strength and smooth price fluctuations in trading, with an ...
Abstract: Defining a sound shift operator for graph signals, similar to the shift operator in classical signal processing, is a crucial problem in graph signal processing (GSP), since almost all ...
All datasets used in the paper are available in the data folder. For example, to run the experiments on one of the the synthetic binary datasets with ER graph, 10 nodes edge ratio 2, and 1000 samples, ...
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