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

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

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 ...

Graph-structured data are pervasive in the real-world such as social networks, molecular graphs and transaction networks.

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.

To achieve this, we pose chip floorplanning as a reinforcement learning problem, and develop an edge-based graph convolutional neural network architecture capable of learning rich and transferable ...

Soo Mee Kim, Jisun Shin, Seungjae Baek, Joo-Hyung Ryu, U-Net Convolutional Neural Network Model for Deep Red Tide Learning Using GOCI, Journal of Coastal Research, Special Issue #90: Advances in ...