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most citedA Deep Dive into Machine Learning Density Functional Theory for Materials Science and Chemistry

115 citations · 121 across the 6 of their papers we have counts for

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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…

cond-mat.mtrl-sci2024

Accelerating Electron Dynamics Simulations through Machine Learned Time Propagators

Karan Shah, Attila Cangi

Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under various external perturbations such as laser fields. In this work, w…