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- W4372260041 abstract "Group convolutional neural networks are a useful tool for utilizing symmetries known to be in a signal; however, they require that the signal is defined on the group itself. Existing approaches either work directly with group signals, or they impose a lifting step with heuristics to compute the convolution which can be computationally costly. Taking an algebraic signal processing perspective, we propose a novel convolutional filter from the Lie group algebra directly, thereby removing the need to lift altogether. Furthermore, we establish stability of the filter by drawing connections to multigraph signal processing. The proposed filter is evaluated on a classification problem on two datasets with SO(3) group symmetries." @default.
- W4372260041 created "2023-05-07" @default.
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- W4372260041 date "2023-06-04" @default.
- W4372260041 modified "2023-09-27" @default.
- W4372260041 title "Algebraic Convolutional Filters on Lie Group Algebras" @default.
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- W4372260041 doi "https://doi.org/10.1109/icassp49357.2023.10095164" @default.
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