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.
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 ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...
This repository is an official PyTorch implementation of "Omni-Dimensional Dynamic Convolution", ODConv for short, published by ICLR 2022 as a spotlight. ODConv is a more generalized yet elegant ...
Researchers developed an Ag/Sb2O3/Au memristor array that mimics brain-like computing, performing on-device image feature extraction with low power consumption, promising smarter and faster electric ...
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph Convolution (AdaptConv) is a point cloud convolution operator presented in our ICCV2021 paper. If you ...
Abstract: Convolution and self-attention are two powerful techniques for multisource remote sensing (RS) data fusion that have been widely adopted in Earth observation tasks. However, convolutional ...
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