A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention ...

Research team led by Chuliang Weng introduces D2-GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation ...

Meiya Pico's patent focuses on classifying social text using Graph Convolutional Networks. GCN is a deep learning model ...

Therefore, we explored a model based on graph convolutional neural networks (GCNN) to perform survival prediction of cancer patients using WSIs. Methods: We utilized WSIs collected from The Cancer ...

We applied three types of established GNN techniques, namely Crystal Graph Convolutional Neural Network (CGCNN), Materials Graph Network (MEGNET), and Atomistic Line Graph Neural Network (ALIGNN), to ...

Without dumping all that's been achieved with things such as "convolutional neural networks," or CNNs, the shining success of machine learning, they propose ways to impart broader reasoning skills.