3 citations · 3 across the 3 of their papers we have counts for
3 papers
eess.SP2024
SLoG-Net: Algorithm Unrolling for Source Localization on Graphs
Chang Ye, Gonzalo Mateos
We present a novel model-based deep learning solution for the inverse problem of localizing sources of network diffusion. Starting from first graph signal processing (GSP) principl…
eess.SP2024
Blind Deconvolution of Graph Signals: Robustness to Graph Perturbations
Chang Ye, Gonzalo Mateos
We study blind deconvolution of signals defined on the nodes of an undirected graph. Although observations are bilinear functions of both unknowns, namely the forward convolutional…
cs.LG2024★ 3 cited
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten +30
In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curv…