collaborators

8 papers

eess.SP2020

Graph-Adaptive Activation Functions for Graph Neural Networks

Bianca Iancu, Luana Ruiz, Alejandro Ribeiro +1

Activation functions are crucial in graph neural networks (GNNs) as they allow defining a nonlinear family of functions to capture the relationship between the input graph data and…

eess.SP2020

Forecasting Multi-Dimensional Processes over Graphs

Alberto Natali, Elvin Isufi, Geert Leus

The forecasting of multi-variate time processes through graph-based techniques has recently been addressed under the graph signal processing framework. However, problems in the rep…

eess.SP2020

Quantization Analysis and Robust Design for Distributed Graph Filters

Leila Ben Saad, Baltasar Beferull-Lozano, Elvin Isufi

Distributed graph filters have found applications in wireless sensor networks (WSNs) to solve distributed tasks such as consensus, signal denoising, and reconstruction. However, wh…

eess.SP2019

State-Space Based Network Topology Identification

Mario Coutino, Elvin Isufi, Takanori Maehara +1

In this work, we explore the state-space formulation of network processes to recover the underlying structure of the network (local connections). To do so, we employ subspace techn…

eess.SP2019

Graph-Time Spectral Analysis for Atrial Fibrillation

Miao Sun, Elvin Isufi, Natasja M. S. de Groot +1

Atrial fibrillation is a clinical arrhythmia with multifactorial mechanisms still unresolved. Time-frequency analysis of epicardial electrograms has been investigated to study atri…

eess.SP2019

State-Space Network Topology Identification from Partial Observations

Mario Coutino, Elvin Isufi, Takanori Maehara +1

In this work, we explore the state-space formulation of a network process to recover, from partial observations, the underlying network topology that drives its dynamics. To do so,…