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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.ET2026

Remotely programming the weights of a spintronic neural network by a radiofrequency broadcast signal

M. Menshawy, D. Sanz-Hernández, L. Mazza +7

The paper demonstrates a method to remotely program the binary weights of a spintronic neural network using broadcast radiofrequency signals, enabling rapid reconfiguration of hard…

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…

cs.LG2025

Self-Contrastive Forward-Forward Algorithm

Xing Chen, Dongshu Liu, Jeremie Laydevant +1

Agents that operate autonomously benefit from lifelong learning capabilities. However, compatible training algorithms must comply with the decentralized nature of these systems, wh…

cond-mat.dis-nn2025

Training a multilayer dynamical spintronic network with standard machine learning tools to perform time series classification

Erwan Plouet, Dédalo Sanz-Hernández, Aymeric Vecchiola +2

The ability to process time-series at low energy cost is critical for many applications. Recurrent neural network, which can perform such tasks, are computationally expensive when…

eess.SP2025

Convolutions with Radio-Frequency Spin-Diodes

Erwann Plouet, Hanuman Singh, Pankaj Sethi +3

The classification of radio-frequency (RF) signals is crucial for applications in robotics, traffic control, and medical devices. Spintronic devices, which respond to RF signals vi…