3 papers
cond-mat.mtrl-sci2026
MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance
Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid +5
Electronic-structure calculations based on Kohn-Sham density functional theory remain indispensable in computational materials science and chemistry. Their computational cost, howe…
physics.chem-ph2025
Scalable Machine Learning Model for Energy Decomposition Analysis in Aqueous Systems
Hossein Tahmasbi, Michael Beerbaum, Bartosz Brzoza +2
Energy decomposition analysis (EDA) based on absolutely localized molecular orbitals provides detailed insights into intermolecular bonding by decomposing the total molecular bindi…
cond-mat.mtrl-sci2024
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations
Attila Cangi, Lenz Fiedler, Bartosz Brzoza +11
We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for…