118 citations · 393 across the 14 of their papers we have counts for
5 papers · 1 filter
Dirichlet Graph Variational Autoencoder
Jia Li, Tomasyu Yu, Jiajin Li +5
Graph Neural Networks (GNNs) and Variational Autoencoders (VAEs) have been widely used in modeling and generating graphs with latent factors. However, there is no clear explanation…
Robust Data Hiding Using Inverse Gradient Attention
Honglei Zhang, Hu Wang, Yuanzhouhan Cao +2
Data hiding is the procedure of encoding desired information into a certain types of cover media (e.g. images) to resist potential noises for data recovery, while ensuring the embe…
Learning to Learn to Compress
Nannan Zou, Honglei Zhang, Francesco Cricri +5
In this paper we present an end-to-end meta-learned system for image compression. Traditional machine learning based approaches to image compression train one or more neural networ…
End-to-End Learning for Video Frame Compression with Self-Attention
Nannan Zou, Honglei Zhang, Francesco Cricri +5
One of the core components of conventional (i.e., non-learned) video codecs consists of predicting a frame from a previously-decoded frame, by leveraging temporal correlations. In…
Adversarial Attack on Community Detection by Hiding Individuals
Jia Li, Honglei Zhang, Zhichao Han +3
It has been demonstrated that adversarial graphs, i.e., graphs with imperceptible perturbations added, can cause deep graph models to fail on node/graph classification tasks. In th…