activity
20182020
most citedSelf-supervised GAN: Analysis and Improvement with Multi-class Minimax Game

41 citations · 50 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2020

On Data Augmentation for GAN Training

Ngoc-Trung Tran, Viet-Hung Tran, Ngoc-Bao Nguyen +2

Recent successes in Generative Adversarial Networks (GAN) have affirmed the importance of using more data in GAN training. Yet it is expensive to collect data in many domains such…

cs.CV201941 cited

Self-supervised GAN: Analysis and Improvement with Multi-class Minimax Game

Ngoc-Trung Tran, Viet-Hung Tran, Ngoc-Bao Nguyen +2

Self-supervised (SS) learning is a powerful approach for representation learning using unlabeled data. Recently, it has been applied to Generative Adversarial Networks (GAN) traini…

cs.CV20199 cited

An Improved Self-supervised GAN via Adversarial Training

Ngoc-Trung Tran, Viet-Hung Tran, Ngoc-Bao Nguyen +1

We propose to improve unconditional Generative Adversarial Networks (GAN) by training the self-supervised learning with the adversarial process. In particular, we apply self-superv…

cs.IT2018

Variational Bayes Inference in Digital Receivers

Viet Hung Tran

The digital telecommunications receiver is an important context for inference methodology, the key objective being to minimize the expected loss function in recovering the transmit…

cs.LG2018

Bayesian inference for PCA and MUSIC algorithms with unknown number of sources

Viet Hung Tran, Wenwu Wang

Principal component analysis (PCA) is a popular method for projecting data onto uncorrelated components in lower dimension, although the optimal number of components is not specifi…

cs.IT2018

Copula Variational Bayes inference via information geometry

Viet Hung Tran

Variational Bayes (VB), also known as independent mean-field approximation, has become a popular method for Bayesian network inference in recent years. Its application is vast, e.g…