GitHub

Graph Structure of Neural Networks

TLDR: We study the architecture of neural networks through the lens of network science, and discover that good neural networks are alike in terms of their underlying graph structure. Overview of our ...
Frontiers

Dual-channel deep graph convolutional neural networks

The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance of ...
IEEE

Text Classification Using Document-Relational Graph Convolutional Networks

Abstract: Graph Convolutional Networks (GCNs) have received considerable attention in the field of artificial machine intelligence (AMI) and natural language processing research because they can build ...
Frontiers

Multi-Dimensional Enhanced Seizure Prediction Framework Based on Graph Convolutional Network

In terms of seizure prediction, how to fully mine relational data information among multiple channels of epileptic EEG? This is a scientific research subject worthy of further exploration. Recently, ...
Scientific Research Publishing

Food Ingredients Identification from Dish Images by Deep Learning ()

Diet plays an important role in people’s daily life with its strong correlation to health and chronic diseases. Meanwhile, deep based food computing emerges to provide lots of works which including ...
IEEE

Tensor Graph Convolutional Networks for Multi-Relational and Robust Learning

Abstract: The era of “data deluge” has sparked renewed interest in graph-based learning methods and their widespread applications ranging from sociology and biology to transportation and ...