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 ...

Modern network-on-chip could include different types of nodes. Generally nodes that are of-chip external interconnections controllers – external nodes, are used in the system for I/O. Internal nodes ...

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...

On Thursday the 24th of August 2023, M.Sc. Arpit Merchant defends his PhD thesis on Applications of Node Embeddings to Learning and Mining on Graphs. The thesis is related to research done in the ...

Efficiently and quickly chewing through one trillion edges of a complex graph is no longer in itself a standalone achievement, but doing so on a single node, albeit with some acceleration and ...