From the 1 of 8 linked papers with an AI index.
8 papers
Physical Reservoir Signal Acquisition for Sub-Nyquist Waveform Reconstruction
Yuito Ito, Anas Skalli, Tetsuya Asai +1
The paper proposes reservoir signal acquisition, using a physical reservoir as a measurement device to transform broadband signals into multiple low‑rate samples, enabling exact or…
Power law scaling for classification accuracy in physical neural networks
Andrei V. Ermolaev, Mathilde Hary, Anas Skalli +7
Physical neural networks (PNNs) harness the intrinsic complexity of physical systems to perform neural computation, potentially at speeds and energy efficiencies inaccessible to co…
The thin line for optical neural networks towards broad practical relevance
Anas Skalli, Daniel Brunner
Optical neural networks promise unmatched efficiency, bandwidth, and latency, critical benefits as demand for neural network hardware surges. However, their practical value for gen…
A spiking photonic neural network of 40.000 neurons, trained with rank-order coding for leveraging sparsity
Ria Talukder, Anas Skalli, Xavier Porte +2
Spiking neural networks are neuromorphic systems that emulate certain aspects of biological neurons, offering potential advantages in energy efficiency and speed by for example lev…
Limits of nonlinear and dispersive fiber propagation for an optical fiber-based extreme learning machine
Andrei V. Ermolaev, Mathilde Hary, Lev Leybov +5
We report a generalized nonlinear Schrödinger equation simulation model of an extreme learning machine (ELM) based on optical fiber propagation. Using the MNIST handwritten digit…
Model-free front-to-end training of a large high performance laser neural network
Anas Skalli, Satoshi Sunada, Mirko Goldmann +5
Artificial neural networks (ANNs), have become ubiquitous and revolutionized many applications ranging from computer vision to medical diagnoses. However, they offer a fundamentall…