Actualités

IEEE2 a
Graph Convolutional Extreme Learning Machine Autoencoder for Graph Embedding
Abstract: The purpose of graph embedding is to encode the known node features ... with a large iterative learning time, and susceptible to local optimal solutions. Thus, we propose Graph Convolutional ...
GitHub7 a
vuptran/graph-representation-learning
This is a Keras implementation of the symmetrical autoencoder architecture with parameter sharing for the tasks of link prediction and semi-supervised node classification, as described in the ...
IEEE8 mois
Combining an Autoencoder and a Variational Autoencoder for Explaining the Machine Learning Model Predictions
Abstract: A method for explaining a deep learning model prediction is proposed. It uses a combination of the standard autoencoder and the variational autoencoder. The standard autoencoder is exploited ...
Huawei2 a
Joint Message Passing and Autoencoder for Deep Learning
This MPA enabling feature would allow not only a coarse learning ... nodes to functional nodes. Before describing the iterative adjusting procedure over a dimension reduction layer, we will introduce ...