In this paper, we propose a physics-guided neural network to solve the PF problem, with an auxiliary task to rebuild the PF model. By encoding different granularity of Kirchhoff's laws, and system ...

Interestingly, the issues uncovered explain how common heuristics for data-fit neural networks (e.g. initialization) cause training difficulties in this new paradigm of PINNs. Critically, we believe ...

As a consequence, orchestrating these abstractions to implement a common network policy becomes an arduous task. To address this challenge, plain data representations of the network and its control ...

Abstract: Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and ...

The proposed model takes a picture of a handwritten text as input and converts it into digital text. The Convolutional Neural Network (CNN) is used to study the features of similar objects from ...

Therefore, we propose an attention-based graph neural network news recommendation model. In our model, muti-channel convolutional neural network is used to generate news representations, and recurrent ...

It now appears that neural nets may be the next frontier in the advance of computing technology as a whole. But what are ...