Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...
In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...
Scholars deliver the first systematic survey of Dynamic GNNs, unifying continuous- and discrete-time models, benchmarking ...
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 ...
Beijing, Jan. 05, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning ...
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 ...
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: An undirected weighted graph (UWG) is the fundamental data representation in various real applications. A graph convolution network is frequently utilized for representation learning to a ...
Covid-19 broke the charts. Decades from now, the pandemic will be visible in the historical data of nearly anything measurable today: an unmistakable spike, dip or jolt that officially began for ...
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