PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience (IMAGE)

The Hong Kong Polytechnic University

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

Caption

Illustration of simplices, boundary operators, and simplex downsampling. Panel (a) illustrates a graph with the 0-, 1-, 2-simplices, while Panel (b) displays its corresponding 1-st and 2-nd boundary operators. Panel (c) demonstrates an example of the simplex downsampling and the update of the corresponding boundary operators. In the simplex assignment matrix, each row corresponds to the k-simplex of the downsampled graph, and each column corresponds to the k-simplex of the original graph.

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