62 citations · 350 across the 33 of their papers we have counts for
3 papers · 2 filters
A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation
Huynh Van Luong, Boris Joukovsky, Yonina C. Eldar +1
Deep unfolded neural networks are designed by unrolling the iterations of optimization algorithms. They can be shown to achieve faster convergence and higher accuracy than their op…
Graph Convolutional Neural Networks with Node Transition Probability-based Message Passing and DropNode Regularization
Tien Huu Do, Duc Minh Nguyen, Giannis Bekoulis +2
Graph convolutional neural networks (GCNNs) have received much attention recently, owing to their capability in handling graph-structured data. Among the existing GCNNs, many metho…
Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted - Minimization: Architecture Design and Generalization Analysis
Huynh Van Luong, Boris Joukovsky, Nikos Deligiannis
Deep unfolding methods---for example, the learned iterative shrinkage thresholding algorithm (LISTA)---design deep neural networks as learned variations of optimization methods. Th…