| Deep dive into machine learning density functional theory for materials science and chemistry L Fiedler, K Shah, M Bussmann, A Cangi Physical Review Materials 6 (4), 040301, 2022 | 73 | 2022 |
| Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks JA Ellis, L Fiedler, GA Popoola, NA Modine, JA Stephens, AP Thompson, ... Physical Review B 104 (3), 035120, 2021 | 69 | 2021 |
| PyFLOSIC: Python-based Fermi–Löwdin orbital self-interaction correction S Schwalbe, L Fiedler, J Kraus, J Kortus, K Trepte, S Lehtola The Journal of Chemical Physics 153 (8), 2020 | 34 | 2020 |
| Interpretation and Automatic Generation of Fermi‐Orbital Descriptors S Schwalbe, K Trepte, L Fiedler, AI Johnson, J Kraus, T Hahn, JE Peralta, ... Journal of Computational Chemistry 40 (32), 2843-2857, 2019 | 32 | 2019 |
| Predicting electronic structures at any length scale with machine learning L Fiedler, NA Modine, S Schmerler, DJ Vogel, GA Popoola, AP Thompson, ... npj Computational Materials 9 (1), 115, 2023 | 31 | 2023 |
| Accelerating equilibration in first-principles molecular dynamics with orbital-free density functional theory L Fiedler, ZA Moldabekov, X Shao, K Jiang, T Dornheim, M Pavanello, ... Physical Review Research 4 (4), 043033, 2022 | 21 | 2022 |
| Training-free hyperparameter optimization of neural networks for electronic structures in matter L Fiedler, N Hoffmann, P Mohammed, GA Popoola, T Yovell, V Oles, ... Machine Learning: Science and Technology 3 (4), 045008, 2022 | 7 | 2022 |
| Machine learning the electronic structure of matter across temperatures L Fiedler, NA Modine, KD Miller, A Cangi Physical Review B 108 (12), 125146, 2023 | 4 | 2023 |
| Predicting the electronic structure of matter on ultra-large scales L Fiedler, N Modine, S Schmerler, DJ Vogel, GA Popoola, A Thompson, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | 2 | 2022 |
| Machine-Learning for Static and Dynamic Electronic Structure Theory L Fiedler, K Shah, A Cangi Machine Learning in Molecular Sciences, 113-160, 2023 | 1 | 2023 |
| Development and Application of Scalable Density Functional Theory Machine Learning Models L Fiedler | | 2024 |
| A machine learning surrogate for density functional theory based on the local density of state. N Modine, L Fiedler, D Vogel, A Thompson, A Ellis, J Stephens, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Size transferability of machine-learning based density functional theory surrogates L Fiedler, G Popoola, N Modine, A Thompson, A Cangi APS March Meeting Abstracts 2022, G01. 008, 2022 | | 2022 |
| Finding Electronic Structure Machine Learning Surrogates without Training L Fiedler, N Hoffmann, P Mohammed, GA Popoola, T Yovell, V Oles, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Electronic Structure Machine Learning Surrogates without Training L Fiedler, N Hoffmann, P Mohammed, GA Popoola, T Yovell, V Oles, ... arXiv e-prints, arXiv: 2202.09186, 2022 | | 2022 |
| An Introduction to the Materials Learning Algorithms Package (MALA). L Fiedler, A Ellis, S Rajamanickam, A Cangi Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | | 2021 |
| Finding Machine-Learning Surrogates for Electronic Structures without Training L Fiedler, N Hoffmann, P Mohammed, GA Popoola, T Yovell, V Oles, ... | | |
| Uncertainty quantification in machine learning applications S Schmerler, S Starke, P Steinbach, QMK Siddiqui, L Fiedler, A Cangi, ... | | |
| Bond order analysis in FLO-SIC K Trepte, S Schwalbe, L Fiedler, AI Johnson, J Kraus, T Hahn, JE Peralta, ... | | |
| Fermi-orbital descriptor generators K Trepte, S Schwalbe, L Fiedler, AI Johnson, J Kraus, T Hahn, JE Peralta, ... | | |
Attila CangiCenter for Advanced Systems Understanding, Helmholtz-Zentrum Dresden-RossendorfEmail verificata su hzdr.de