Graph-based learning techniques traditionally focus on pairwise relationships, modelling them as edges between two nodes. Hypergraphs generalise this concept by allowing edges—known as hyperedges—to ...
Background: Molecular interactions are central to numerous challenges in chemistry and the life sciences. Whether in solute–solvent dissolution, adverse drug–drug interactions, or protein complex ...
A new technical paper titled “A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware” was published by researchers at Politecnico di Milano. “Executing Spiking Neural Networks (SNNs) on ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results