892 citations · 1.1k across the 23 of their papers we have counts for
5 papers · 1 filter
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection
Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen +3
Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks. It, however, is also a challenging step that requires speci…
Quaternion Graph Neural Networks
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Recently, graph neural networks (GNNs) have become an important and active research direction in deep learning. It is worth noting that most of the existing GNN-based methods learn…
A Self-Attention Network based Node Embedding Model
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Despite several signs of progress have been made recently, limited research has been conducted for an inductive setting where embeddings are required for newly unseen nodes -- a se…
A Capsule Network-based Model for Learning Node Embeddings
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen +1
In this paper, we focus on learning low-dimensional embeddings for nodes in graph-structured data. To achieve this, we propose Caps2NE -- a new unsupervised embedding model leverag…
Universal Graph Transformer Self-Attention Networks
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
We introduce a transformer-based GNN model, named UGformer, to learn graph representations. In particular, we present two UGformer variants, wherein the first variant (publicized i…