Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
Abstract: Visual retrieval tasks such as image retrieval and person re-identification (Re-ID) aim at effectively and thoroughly searching images with similar content or the same identity. After ...
Implementation of Crystal Edge Graph Attention Neural Network (CEGANN) workflow that uses graph attention-based architecture to perform multiscale classification of materials. Copy CEGAN code in the ...
the main.py can be run from the command line interface with the following commands, where -f (dataset file) and -r (the number of parid replicates) are the two required parameters. An example command ...
A lot of combinatorial objects have a natural bialgebra structure. In this paper, we prove that the vector space spanned by labeled simple graphs is a bialgebra with the conjunction product and the ...
In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, ...
The automatic identification of the topology of power networks is important for the data-driven and situation-aware operation of power grids. Traditional methods of topology identification lack a data ...
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