2 papers
cond-mat.str-el2025
Concentration-Free Quantum Kernel Learning in the Rydberg Blockade
Ayana Sarkar, Martin Schnee, Sangeeth Das Kallullathil +4
Quantum kernel methods (QKMs) offer an appealing framework for machine learning on near-term quantum computers. However, QKMs generically suffer from exponential concentration, req…
quant-ph2024
Fermionic Machine Learning
Jérémie Gince, Jean-Michel Pagé, Marco Armenta +2
We introduce fermionic machine learning (FermiML), a machine learning framework based on fermionic quantum computation. FermiML models are expressed in terms of parameterized match…