Abstract: In this paper, we present a novel convolution theorem which encompasses the well known convolution theorem in (graph) signal processing as well as the one related to time-varying filters.
Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a chip that could change everything by using light instead of electricity for a ...
Abstract: Attributed graph clustering is of significance for an in-depth understanding of the intrinsic organization of complex networks. Recently, owing to the powerful learning capability of deep ...
Emergency departments (EDs) are critical healthcare settings that often face challenges related to patient overcrowding and sub-optimal resource use, and these issues have been linked to reduced ...
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