Recent advances in relation extraction with deep neural architectures have achieved excellent performance. However, current models still suffer from two main drawbacks: 1) they require enormous ...

This letter introduces a novel physics-informed approach for neural network-based 3-D electromagnetic modeling. The proposed method combines standard leap-frog time-stepping with neural network-driven ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.