22 citations · 61 across the 30 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
Cell Attention Networks
Lorenzo Giusti, Claudio Battiloro, Lucia Testa +3
Since their introduction, graph attention networks achieved outstanding results in graph representation learning tasks. However, these networks consider only pairwise relationships…
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…
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…