13 citations · 35 across the 16 of their papers we have counts for
17 papers
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…
Approximating velocity fields with planted attractors via Neural-ODEs for classification purposes
Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni +3
In this work, Neural ODEs equipped with a curated collection of equilibrium points have been successfully employed for classification tasks. The planted attractors serve as indicat…
Exact Fixed-Point Constraints in Neural-ODEs with Provable Universality
Feliciano Giuseppe Pacifico, Duccio Fanelli, Lorenzo Buffoni +3
We introduce a technique that enables Neural-ODEs to approximate arbitrary velocity fields with a priori planted fixed-points. Specifically, a recipe is given to explicitly accommo…
Train Stochastic Non Linear Coupled ODEs to Classify and Generate
Stefano Gagliani, Feliciano Giuseppe Pacifico, Lorenzo Chicchi +4
A general class of dynamical systems which can be trained to operate in classification and generation modes are introduced. A procedure is proposed to plant asymptotic stationary a…
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…
A short introduction to Neural Networks and their application to Earth and Materials Science Science
Duccio Fanelli, Luca Bindi, Lorenzo Chicchi +3
Neural networks are gaining widespread relevance for their versatility, holding the promise to yield a significant methodological shift in different domain of applied research. Her…
Learning in Wilson-Cowan model for metapopulation
Raffaele Marino, Lorenzo Buffoni, Lorenzo Chicchi +4
The Wilson-Cowan model for metapopulation, a Neural Mass Network Model, treats different subcortical regions of the brain as connected nodes, with connections representing various…
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…
Stable Attractors for Neural networks classification via Ordinary Differential Equations (SA-nODE)
Raffaele Marino, Lorenzo Giambagli, Lorenzo Chicchi +2
A novel approach for supervised classification is presented which sits at the intersection of machine learning and dynamical systems theory. At variance with other methodologies th…
Recurrent Spectral Network (RSN): shaping the basin of attraction of a discrete map to reach automated classification
Lorenzo Chicchi, Duccio Fanelli, Lorenzo Giambagli +2
A novel strategy to automated classification is introduced which exploits a fully trained dynamical system to steer items belonging to different categories toward distinct asymptot…
On the training of sparse and dense deep neural networks: less parameters, same performance
Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni +3
Deep neural networks can be trained in reciprocal space, by acting on the eigenvalues and eigenvectors of suitable transfer operators in direct space. Adjusting the eigenvalues, wh…
Mobility-based prediction of SARS-CoV-2 spreading
Lorenzo Chicchi, Lorenzo Giambagli, Lorenzo Buffoni +1
The rapid spreading of SARS-CoV-2 and its dramatic consequences, are forcing policymakers to take strict measures in order to keep the population safe. At the same time, societal a…
Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging
Lorenzo Chicchi, Gloria Cecchini, Ihusan Adam +7
An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire…