Explores multipole expansion in electrostatics and magnetostatics, focusing on monopole, dipole, and higher-order moments, and their mathematical representations.
Explores atomic descriptors, emphasizing symmetry, locality, and the challenges of incorporating electrostatics in machine learning models for chemistry.
Explores applying machine learning to atomic scale systems, emphasizing symmetry in feature mapping and the construction of rotationally invariant descriptors.
