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Found 4 papers, 1 papers with code
PET-MAD, a universal interatomic potential for advanced materials modeling
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 the effort.
Unified theory of atom-centered representations and message-passing machine-learning schemes
Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents.
Optimal radial basis for density-based atomic representations
For each training dataset and number of basis functions, one can determine a unique basis that is optimal in this sense, and can be computed at no additional cost with respect to the primitive basis by approximating it with splines.
Recursive evaluation and iterative contraction of $N$-body equivariant features
While it has become clear that low-order density correlations do not provide a complete representation of an atomic environment, the exponential increase in the number of possible $N$-body invariants makes it difficult to design a concise and effective representation.
Chemical Physics
