As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Announcing a new publication for Acta Materia Medica journal. Traditional Chinese medicine has shown therapeutic potential in ...
Complex-valued Hopfield neural networks extend the classical Hopfield model by allowing neuron activations and synaptic weights to assume complex values. This generalisation enables the encoding of ...
As one of the most crucial topics in the recommendation system field, Point-of-Interest (POI) recommendation aims to recommending potential interesting POIs to users. Recently, graph neural networks ...
The Optum Enterprise and Data Analytics (EDA) Graph & Health @ Scale (GHS) team is happy to announce v1.0 of our g2gnn library. In this presentation we will discuss the g2gnn library, how it works, ...
While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...
In our view, higher-category theory, which possesses the highest degree of abstraction, is a second-level language relative ...
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