30 citations · 31 across the 21 of their papers we have counts for
9 papers · 1 filter
Learning-Based Reconstruction of Optical Properties in Bilayered Media from Single-distance Time-Resolved Reflectance Measurements
Caterina Amendola, Giulia Maffeis, Lorenzo Buffoni +8
The inverse problem of reconstructing optical properties, specifically absorption and scattering coefficients, in layered biological media from time-domain reflectance measurements…
Spectral Higher-Order Neural Networks Have Sharp Expressivity Bounds
Gianluca Peri, Diego Febbe, Duccio Fanelli
Neural hypergraphs are a natural generalization of neural networks, the reference models in modern machine learning. Yet, their deployment has proven demanding: the number of weigh…
Spectral Higher-Order Neural Networks
Gianluca Peri, Timoteo Carletti, Duccio Fanelli +1
Neural networks are fundamental tools of modern machine learning. The standard paradigm assumes binary interactions (across feedforward linear passes) between inter-tangled units,…
Spectral Architecture Search for Neural Network Models
Gianluca Peri, Lorenzo Chicchi, Duccio Fanelli +1
Architecture design and optimization are challenging problems in the field of artificial neural networks. Working in this context, we here present SPARCS (SPectral ARchiteCture Sea…
Deterministic versus stochastic dynamical classifiers: opposing random adversarial attacks with noise
Lorenzo Chicchi, Duccio Fanelli, Diego Febbe +4
The Continuous-Variable Firing Rate (CVFR) model, widely used in neuroscience to describe the intertangled dynamics of excitatory biological neurons, is here trained and tested as…
Estimating Global Input Relevance and Enforcing Sparse Representations with a Scalable Spectral Neural Network Approach
Lorenzo Chicchi, Lorenzo Buffoni, Diego Febbe +3
In machine learning practice it is often useful to identify relevant input features. Isolating key input elements, ranked according their respective degree of relevance, can help t…
Complex Recurrent Spectral Network
Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni +2
This paper presents a novel approach to advancing artificial intelligence (AI) through the development of the Complex Recurrent Spectral Network (-RSN), an innovative v…
Engineered Ordinary Differential Equations as Classification Algorithm (EODECA): thorough characterization and testing
Raffaele Marino, Lorenzo Buffoni, Lorenzo Chicchi +2
EODECA (Engineered Ordinary Differential Equations as Classification Algorithm) is a novel approach at the intersection of machine learning and dynamical systems theory, presenting…
How a student becomes a teacher: learning and forgetting through Spectral methods
Lorenzo Giambagli, Lorenzo Buffoni, Lorenzo Chicchi +1
In theoretical ML, the teacher-student paradigm is often employed as an effective metaphor for real-life tuition. The above scheme proves particularly relevant when the student net…