Interpretation and Automatic Generation of Fermi-Orbital Descriptors. - Sebastian Schwalbe; Kai Trepte; Lenz Fiedler; Alex I. Johnson; Jakob Kraus; Torsten Hahn; Juan E. Peralta; Koblar A. Jackson; Jens Kortus (J. Comput. Chem., 2019)

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry. - Lenz Fiedler; Karan Shah 001; Attila Cangi; Michael Bussmann (RODARE, 2021)

Dataset and scripts for A Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry. - Lenz Fiedler; Karan Shah 001; Attila Cangi; Michael Bussmann (RODARE, 2021)

Scripts and Models for "Predicting electronic structures at any length scale with machine learning". - Lenz Fiedler; Steve Schmerler; Normand A. Modine; Dayton J. Vogel; Gabriel A. Popoola; Aidan P. Thompson; Sivasankaran Rajamanickam; Attila Cangi (RODARE, 2022)

Training-free hyperparameter optimization of neural networks for electronic structures in matter. - Lenz Fiedler; Nils Hoffmann; Parvez Mohammed; Gabriel A. Popoola; Tamar Yovell; Vladyslav Oles; J. Austin Ellis; Sivasankaran Rajamanickam; Attila Cangi (Mach. Learn. Sci. Technol., 2022)

Development and Application of Scalable Density Functional Theory Machine Learning Models - Lenz Fiedler (2024)

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations. - Attila Cangi; Lenz Fiedler; Bartosz Brzoza; Karan Shah 001; Timothy J. Callow; Daniel Kotik; Steve Schmerler; Matthew C. Barry; James M. Goff; Andrew Rohskopf; Dayton J. Vogel; Normand A. Modine; et al. (Comput. Phys. Commun., 2025)