most citedSimplicial Attention Neural Networks

12 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

eess.SP2022

Tangent Bundle Filters and Neural Networks: from Manifolds to Cellular Sheaves and Back

Claudio Battiloro, Zhiyang Wang, Hans Riess +2

In this work we introduce a convolution operation over the tangent bundle of Riemannian manifolds exploiting the Connection Laplacian operator. We use the convolution to define tan…

eess.SP20221 cited

Topological Slepians: Maximally Localized Representations of Signals over Simplicial Complexes

Claudio Battiloro, Paolo Di Lorenzo, Sergio Barbarossa

This paper introduces topological Slepians, i.e., a novel class of signals defined over topological spaces (e.g., simplicial complexes) that are maximally concentrated on the topol…

eess.SP20221 cited

Pooling Strategies for Simplicial Convolutional Networks

Domenico Mattia Cinque, Claudio Battiloro, Paolo Di Lorenzo

The goal of this paper is to introduce pooling strategies for simplicial convolutional neural networks. Inspired by graph pooling methods, we introduce a general formulation for a…

eess.SP2022

Energy-Efficient Classification at the Wireless Edge with Reliability Guarantees

Mattia Merluzzi, Claudio Battiloro, Paolo Di Lorenzo +1

Learning at the edge is a challenging task from several perspectives, since data must be collected by end devices (e.g. sensors), possibly pre-processed (e.g. data compression), an…

cs.LG202212 cited

Simplicial Attention Neural Networks

L. Giusti, C. Battiloro, P. Di Lorenzo +2

The aim of this work is to introduce simplicial attention networks (SANs), i.e., novel neural architectures that operate on data defined on simplicial complexes leveraging masked s…

eess.SP2020

Dynamic Resource Optimization for Decentralized Estimation in Energy Harvesting IoT Networks

C. Battiloro, P. Di Lorenzo, P. Banelli +1

We study decentralized estimation of time-varying signals at a fusion center, when energy harvesting sensors transmit sampled data over rate-constrained links. We propose dynamic s…