3 papers
cs.LG2026
Understanding and inverse design of implicit bias in stochastic learning: a geometric perspective
Nicola Aladrah, Emanuele Ballarin, Matteo Biagetti +3
A key challenge in machine learning is to explain how learning dynamics select among the many solutions that achieve identical loss values in overparameterized models - a phenomeno…
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…