activity
20232026
most citedIntrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations

1 citations · 1 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

The Dynamics of Discoverability: How Trajectories and Priors Shape Equation Recovery

Matteo Gallo, Fabio Anselmi, Paolo Lazzari

How the dynamical regime of the observed system affects equation discovery has mainly been investigated through comparisons across systems. However, such comparisons vary both the…

cs.LG2026

PAC--Bayes Bounds on Quotient Parameter Spaces: Geometry-induced Implicit-Bias Priors

Nicola Aladrah, Fabio Anselmi

Overparameterized models often have continuous parameter symmetries, so different parameters define the same predictor. We show that PAC--Bayesian analysis should be performed on t…

cs.LG2026

Understanding and inverse design of implicit bias in stochastic learning: a geometric perspective

Nicola Aladrah, Emanuele Ballarin, Matteo Biagetti +3

Can we design a model such that its stochastic training favours a desired class of solutions without enforcing an explicit penalty? Under suitable conditions, the interplay between…

quant-ph2024

Decoherence Cancellation through Noise Interference

Giuseppe D'Auria, Giovanna Morigi, Fabio Anselmi +1

We propose a novel, feedback-free method to cancel the effects of decoherence in the dynamics of open quantum systems subject to dephasing. The protocol makes use of the coupling w…

cs.LG2024★ 1 cited

Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations

Lorenzo Basile, Santiago Acevedo, Luca Bortolussi +2

To gain insight into the mechanisms behind machine learning methods, it is crucial to establish connections among the features describing data points. However, these correlations o…

quant-ph2023

Machine Learning Catalysis of Quantum Tunneling

Renzo Testa, Alex Rodriguez, Alberto d'Onofrio +3

Optimizing the probability of quantum tunneling between two states, while keeping the resources of the underlying physical system constant, is a task of key importance due to its c…

quant-ph2023

Catalysis of quantum tunneling by ancillary system learning

Renzo Testa, Alex Rodriguez, Alberto d'Onofrio +3

Given the key role that quantum tunneling plays in a wide range of applications, a crucial objective is to maximize the probability of tunneling from one quantum state/level to ano…

cs.NE2023

Local Search, Semantics, and Genetic Programming: a Global Analysis

Fabio Anselmi, Mauro Castelli, Alberto d'Onofrio +3

Geometric Semantic Geometric Programming (GSGP) is one of the most prominent Genetic Programming (GP) variants, thanks to its solid theoretical background, the excellent performanc…

cs.LG2023

Frequency maps reveal the correlation between Adversarial Attacks and Implicit Bias

Lorenzo Basile, Nikos Karantzas, Alberto d'Onofrio +4

Despite their impressive performance in classification tasks, neural networks are known to be vulnerable to adversarial attacks, subtle perturbations of the input data designed to…