Abstract: Generalized principal component analysis (GPCA) has been an active area of research in statistical signal processing for decades. It is used, e.g., for denoising in subspace tracking as the ...
The theory of totally disconnected locally compact (t.d.l.c.)~groups has advanced considerably in recent years. Lie groups over the valued fields ℚ p of p-adic numbers and 𝔽 q ((X)) of formal Laurent ...
Abstract: Generalized eigenvector plays an essential role in the signal processing field. In this paper, we present a novel neural network learning algorithm for estimating the generalized eigenvector ...
tl;dr: We provably improve GNN expressivity by enhancing message passing with substructure encodings. Our method allows incorporating domain specific prior knowledge and can be used as a drop-in ...
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