The introduction of SPDManifolds and the unique layers of SPDNet revolutionize neural architectures, enhancing performance through novel theoretical advancements in deep learning structures.
Although significant advancements have been made on SPD and Grassmann manifolds for DNNs, a common limitation remains: they do not provide essential mathematical tools for building these networks.
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