Tag: graph convolutional networks

Researchers have built a deep learning model that fuses stock prices, technical indicators, financial news sentiment, and dynamically updated inter-stock ...

Researchers at Fuzhou University have developed RCGELM-AE, a graph embedding model that trains in closed form without gradient descent while ...

A new hybrid model called TG-Parser combines Transformer encoders with graph convolutional networks to achieve record-setting accuracy in English grammatical ...

Researchers have developed AGSL-Gait, a framework that learns adaptive graph structures from skeletal walking data to capture fine-grained joint dependencies, ...

Researchers have built a hybrid recommender system that combines a deep denoising graph convolutional autoencoder, demographic side information, and learning ...

A new graph convolution Transformer framework with self-distillation improves multi-view graph clustering by suppressing cross-view noise and exploiting complementary information ...

Sleep is one of the most intensively studied states of the human body, yet the clinical workhorse used to assess ...