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 ...
Abstract: With the rapid progress in data-driven approaches, artificial intelligence, and big data analytics technologies, utilizing electroencephalogram (EEG) signals for emotion analysis in the ...
Abstract: As a typical spatiotemporal series prediction task, traffic flow prediction has found wide application in intelligent transportation systems (ITS). Despite some progress, several unresolved ...
MicroCloud Hologram ’s approach uses a logarithmic encoding method to reduce the number of qubits needed, representing an N-dimensional feature space using just log (N) qubits. The system forms an end ...
¹ SANKEN, The University of Osaka, Mihogaoka 8-1, Ibaraki, Osaka, 567-0047, JAPAN ² Graduate School of Information Science and Technology, The University of Osaka, Yamadaoka 1-5, Suita, 565-0871, ...
\textit{Graph neural networks} (GNNs) have seen widespread usage across multiple real-world applications, yet in transductive learning, they still face challenges in accuracy, efficiency, and ...
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 ...
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