69 citations · 100 across the 5 of their papers we have counts for
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Predicting nonlinear optical scattering with physics-driven neural networks
Carlo Gigli, Amirhossein Saba, Ahmed Bassam Ayoub +1
Deep neural networks trained on physical losses are emerging as promising surrogates of nonlinear numerical solvers. These tools can predict solutions of Maxwell's equations and co…
Physics-informed neural networks for diffraction tomography
Amirhossein Saba, Carlo Gigli, Ahmed B. Ayoub +1
We propose a physics-informed neural network as the forward model for tomographic reconstructions of biological samples. We demonstrate that by training this network with the Helmh…
Optical Diffraction Tomography based on 3D Physics-Inspired Neural Network (PINN)
Ahmed B. Ayoub, Amirhossein Saba, Carlo Gigli +1
Optical diffraction tomography (ODT) is an emerging 3D imaging technique that is used for the 3D reconstruction of the refractive index (RI) for semi-transparent samples. Various i…