49 citations · 49 across the 1 of their papers we have counts for
3 papers
physics.chem-ph2021★ 49 cited
Efficient implementation of atom-density representations
Félix Musil, Max Veit, Alexander Goscinski +5
Physically-motivated and mathematically robust atom-centred representations of molecular structures are key to the success of modern atomistic machine learning (ML) methods. They l…
physics.comp-ph2020
The role of feature space in atomistic learning
Alexander Goscinski, Guillaume Fraux, Giulio Imbalzano +1
Eficient, physically-inspired descriptors of the structure and composition of molecules and materials play a key role in the application of machine-learning techniques to atomistic…
quant-ph2018
The parallel Grover as dynamic system
Alexander Goscinski
A sequential application of the Grover algorithm to solve the iterated search problem has been improved by Ozhigov by parallelizing the application of the oracle. In this work a re…