122 citations · 396 across the 21 of their papers we have counts for
37 papers
Separation-Free Spectral Super-Resolution via Convex Optimization
Zai Yang, Yi-Lin Mo, Gongguo Tang +1
Atomic norm methods have recently been proposed for spectral super-resolution with flexibility in dealing with missing data and miscellaneous noises. A notorious drawback of these…
KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution
Jiahong Fu, Hong Wang, Qi Xie +3
Although current deep learning-based methods have gained promising performance in the blind single image super-resolution (SISR) task, most of them mainly focus on heuristically co…
A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation
Heran Yang, Jian Sun, Liwei Yang +1
Cross-contrast image translation is an important task for completing missing contrasts in clinical diagnosis. However, most existing methods learn separate translator for each pair…
Understanding Deep MIMO Detection
Qiang Hu, Feifei Gao, Hao Zhang +2
Incorporating deep learning (DL) into multiple-input multiple-output (MIMO) detection has been deemed as a promising technique for future wireless communications. However, most DL-…
Training Networks in Null Space of Feature Covariance for Continual Learning
Shipeng Wang, Xiaorong Li, Jian Sun +1
In the setting of continual learning, a network is trained on a sequence of tasks, and suffers from catastrophic forgetting. To balance plasticity and stability of network in conti…
Learning adaptive differential evolution algorithm from optimization experiences by policy gradient
Jianyong Sun, Xin Liu, Thomas Bäck +1
Differential evolution is one of the most prestigious population-based stochastic optimization algorithm for black-box problems. The performance of a differential evolution algorit…