IEEE

Contra Harmonic Mean Labeling of Some Graphs and Python-Based Continuous-Time Neural Networks for Solving the Travelling Salesman Problem in Artificial Intelligence

Abstract: In this paper, we prove Contra Harmonic Mean Labeling for some star related graphs such as $\mathrm{K}_{1, \mathrm{n}}, S(\mathrm{K}_{1, \mathrm{n ...
Hosted on MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Oak Ridge National Lab

GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism...

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...
Scientific Research Publishing

Defferrard, M., Bresson, X. and Vandergheynst, P. (2016) Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. ArXiv: 1606.09375.

ABSTRACT: Node of network has lots of information, such as topology, text and label information. Therefore, node classification is an open issue. Recently, one vector of node is directly connected at ...
AZoOptics

New Tutorial Explores Artificial Neural Networks in Photonics

The fusion of artificial neural networks (NNs) with photonics has generated significant implications across various scientific fields and industries. A new tutorial review published in the journal ...
IEEE

Implementing Graph Neural Networks Over Wireless Networks via Over-the-Air Computing: A Joint Communication and Computation Framework

Abstract: A Graph Neural Network (GNN) conducts the graph convolution for structured data and obtains the weighted sum over the vertices according to its graph structure. However, in the context of a ...