3 papers
quant-ph2026
Training the parametric interactions in an analog bosonic quantum neural network with Fock basis measurement
Julien Dudas, Baptiste Carles, Elie Gouzien +2
Quantum neural networks promise to extend the power of machine learning into the quantum domain, with potential applications ranging from automatic recognition of quantum states to…
quant-ph2026
Experimental quantum reservoir computing with a circuit quantum electrodynamics system
Baptiste Carles, Julien Dudas, Léo Balembois +2
Quantum reservoir computing is a machine learning framework that offers ease of training compared to other quantum neural networks, as it does not rely on gradient-based optimizati…
physics.app-ph2024
Training of Physical Neural Networks
Ali Momeni, Babak Rahmani, Benjamin Scellier +25
Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research…