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 ...
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 ...
HackerNoon, the community-driven technology publishing platform, today announced the launch of the Proof of Usefulness ...
Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already ...
AZoRobotics on MSN
AI can design heart disease treatments using imaging and biological data
CardioKG could enhance drug discovery for heart disease by integrating imaging data and biological information, improving ...
Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already ...
Abstract: Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on ...
I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. Jul 03, 2025, 10:43am EDT Business 3d tablet virtual growth ...
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