Tucker decomposition is widely used for image representation, data reconstruction, and machine learning tasks, but the calculation cost for updating the Tucker core is high. Bilevel form of triple ...

Abstract: We present a novel deep hypergraph modeling architecture (called DHM-Net) for feature matching in this paper. Our network focuses on learning reliable correspondences between two sets of ...

Graph representations of solid state materials that encode only interatomic-distance information lack geometrical resolution, resulting in degenerate representations that may map distinct structures ...

Deep hypergraph U-Net for brain graph embedding and classification code by Mert Lostar. Please contact mertlostar@gmail.com for inquiries. Thanks. Recently, there has been a surge of interest in deep ...