In this work, graph neural networks (GNNs) and transfer learning are leveraged to transfer device sizing knowledge learned from data of related analog circuit topologies to predict the performance of ...

The effectiveness of graph convolutional networks (GCNs) has been widely demonstrated in skeleton-based action recognition. However, most existing GCN-based methods use a dense adjacency matrix to ...

This useful study presents a biologically realistic, large-scale cortical model of the rat's non-barrel somatosensory cortex, investigating synaptic plasticity of excitatory connections under varying ...