| A newcomer’s guide to deep learning for inverse design in nano-photonics A Khaireh-Walieh, D Langevin, P Bennet, O Teytaud, A Moreau, ... Nanophotonics 12 (24), 4387-4414, 2023 | 13 | 2023 |
| Inverse design with flexible design targets via deep learning: Tailoring of electric and magnetic multipole scattering from nano-spheres A Estrada-Real, A Khaireh-Walieh, B Urbaszek, PR Wiecha Photonics and Nanostructures-Fundamentals and Applications 52, 101066, 2022 | 11 | 2022 |
| Monitoring MBE substrate deoxidation via RHEED image-sequence analysis by deep learning A Khaireh-Walieh, A Arnoult, S Plissard, PR Wiecha Crystal Growth & Design 23 (2), 892-898, 2023 | 8 | 2023 |
| Illustrated tutorial on global optimization in nanophotonics P Bennet, D Langevin, C Essoual, A Khaireh-Walieh, O Teytaud, ... JOSA B 41 (2), A126-A145, 2024 | 3 | 2024 |
| PyMoosh: a comprehensive numerical toolkit for computing the optical properties of multilayered structures D Langevin, P Bennet, A Khaireh-Walieh, P Wiecha, O Teytaud, A Moreau JOSA B 41 (2), A67-A78, 2024 | 1 | 2024 |
