51 citations · 59 across the 3 of their papers we have counts for
3 papers
Choosing the parameter of the Fermat distance: navigating geometry and noise
Frédéric Chazal, Laure Ferraris, Pablo Groisman +3
The Fermat distance has been recently established as a useful tool for machine learning tasks when a natural distance is not directly available to the practitioner or to improve th…
Nonhomogeneous Euclidean first-passage percolation and distance learning
Pablo Groisman, Matthieu Jonckheere, Facundo Sapienza
Consider an i.i.d. sample from an unknown density function supported on an unknown manifold embedded in a high dimensional Euclidean space. We tackle the problem of learning a dist…
Correlations as a resource in quantum thermodynamics
Facundo Sapienza, Federico Cerisola, Augusto J. Roncaglia
The presence of correlations in physical systems can be a valuable resource for many quantum information tasks. They are also relevant in thermodynamic transformations, and their c…