Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems. - Derick Nganyu Tanyu; Jianfeng Ning; Tom Freudenberg; Nick Heilenkötter; Andreas Rademacher; Uwe Iben; Peter Maass (CoRR, 2022)

A Direct Sampling-Based Deep Learning Approach for Inverse Medium Scattering Problems. - Jianfeng Ning; Fuqun Han; Jun Zou 003 (CoRR, 2023)

Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches. - Derick Nganyu Tanyu; Jianfeng Ning; Andreas Hauptmann; Bangti Jin; Peter Maass (CoRR, 2023)

Constructing probing functions for direct sampling methods for inverse scattering problems with limited-aperture data: Finite space framework and deep probing network. - Jianfeng Ning; Jun Zou 003 (J. Comput. Phys., 2025)

A Direct Sampling Method and Its Integration with Deep Learning for Inverse Scattering Problems with Phaseless Data. - Jianfeng Ning; Fuqun Han; Jun Zou 003 (SIAM J. Sci. Comput., 2025)