4 papers
A universal machine learning model for the electronic density of states
Wei Bin How, Pol Febrer, Sanggyu Chong +5
In the last few years several ``universal'' interatomic potentials have appeared, using machine-learning approaches to predict energy and forces of atomic configurations with arbit…
Mechanistic study of mixed lithium halides solid state electrolytes
Davide Tisi, Sergey Pozdnyakov, Michele Ceriotti
Lithium halides with the general formula LiMX, where M indicates metal ions and X halide anions are very actively studied as solid-state electrolytes, because of relati…
Lookup multivariate Kolmogorov-Arnold Networks
Sergey Pozdnyakov, Philippe Schwaller
High-dimensional linear mappings, or linear layers, dominate both the parameter count and the computational cost of most modern deep-learning models. We introduce a general-purpose…
PET-MAD, a lightweight universal interatomic potential for advanced materials modeling
Arslan Mazitov, Filippo Bigi, Matthias Kellner +6
Machine-learning interatomic potentials (MLIPs) have greatly extended the reach of atomic-scale simulations, offering the accuracy of first-principles calculations at a fraction of…