12 citations · 18 across the 13 of their papers we have counts for
9 papers · 1 filter
Topological Adaptive Least Mean Squares Algorithms over Simplicial Complexes
Lorenzo Marinucci, Claudio Battiloro, Paolo Di Lorenzo
This paper introduces a novel adaptive framework for processing dynamic flow signals over simplicial complexes, extending classical least-mean-squares (LMS) methods to high-order t…
Topological Dictionary Learning
Enrico Grimaldi, Claudio Battiloro, Paolo Di Lorenzo
The aim of this paper is to introduce a novel dictionary learning algorithm for sparse representation of signals defined over combinatorial topological spaces, specifically, regula…
Towards a Health-Based Power Grid Optimization in the Artificial Intelligence Era
Claudio Battiloro, Gianluca Guidi, Falco J. Bargagli-Stoffi +1
The electric power sector is one of the largest contributors to greenhouse gas emissions in the world. In recent years, there has been an unprecedented increase in electricity dema…
Goal-oriented Communications for the IoT: System Design and Adaptive Resource Optimization
Paolo Di Lorenzo, Mattia Merluzzi, Francesco Binucci +4
Internet of Things (IoT) applications combine sensing, wireless communication, intelligence, and actuation, enabling the interaction among heterogeneous devices that collect and pr…
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…