20 citations · 128 across the 19 of their papers we have counts for
3 papers · 1 filter
On Node Features for Graph Neural Networks
Chi Thang Duong, Thanh Dat Hoang, Ha The Hien Dang +2
Graph neural network (GNN) is a deep model for graph representation learning. One advantage of graph neural network is its ability to incorporate node features into the learning pr…
Parallel Computation of Graph Embeddings
Chi Thang Duong, Hongzhi Yin, Thanh Dat Hoang +4
Graph embedding aims at learning a vector-based representation of vertices that incorporates the structure of the graph. This representation then enables inference of graph propert…
Weakly Supervised Active Learning with Cluster Annotation
Fábio Perez, Rémi Lebret, Karl Aberer
In this work, we introduce a novel framework that employs cluster annotation to boost active learning by reducing the number of human interactions required to train deep neural net…