how to select the neural-network architecture; and how synthetic data can improve convolutional-neural-network performance. The concept of a perception neural network was first described as ...

Despite five decades of research1, chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to ... and develop an edge-based graph convolutional neural ...

The recent launch of TensorFlow GNN offers a streamlined way to design ... example social networks, recommendation systems, physics simulations, and so on. GNNs extend the foundational ideas of ...

Interestingly, this process is very similar to how convolutional neural networks extract features from pixel data. Accordingly, one very popular GNN architecture is the graph convolutional neural ...