Pushing the limits of optical information storage using deep learning. - Peter R. Wiecha; Aurélie Lecestre; Nicolas Mallet; Guilhem Larrieu (CoRR, 2018)

pyGDM - A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures. - Peter R. Wiecha (Comput. Phys. Commun., 2018)

Monitoring MBE substrate deoxidation via RHEED image-sequence analysis by deep learning. - Abdourahman Khaireh-Walieh; Alexandre Arnoult; Sébastien Plissard; Peter R. Wiecha (CoRR, 2022)

"pyGDM" - new functionalities and major improvements to the python toolkit for nano-optics full-field simulations. - Peter R. Wiecha; Clément Majorel; Arnaud Arbouet; Adelin Patoux; Yoann Brûlé; Gérard Colas des Francs; Christian Girard (Comput. Phys. Commun., 2022)

Ellawin/tuto_global_optimization_photonics: v1. - Pauline Bennet; Olivier Teytaud; Peter R. Wiecha; Denis Langevin; Antoine Moreau; Abdourahman Khaireh-Walieh (Zenodo, 2023)

Programmable metasurfaces for future photonic artificial intelligence. - Loubnan Abou-Hamdan; Emil Marinov; Peter R. Wiecha; Philipp del Hougne; Tianyu Wang; Patrice Genevet (CoRR, 2025)