49 citations · 105 across the 4 of their papers we have counts for
10 papers
Quantum dynamics using path integral coarse-graining
Félix Musil, Iryna Zaporozhets, Frank Noé +2
Vibrational spectra of condensed and gas-phase systems containing light nuclei are influenced by their quantum-mechanical behaviour. The quantum dynamics of light nuclei can be app…
Optimal radial basis for density-based atomic representations
Alexander Goscinski, Félix Musil, Sergey Pozdnyakov +1
The input of almost every machine learning algorithm targeting the properties of matter at the atomic scale involves a transformation of the list of Cartesian atomic coordinates in…
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-inspired structural representations for molecules and materials
Felix Musil, Andrea Grisafi, Albert P. Bartók +3
The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic scale structure of matter and…
Machine learning at the atomic-scale
Félix Musil, Michele Ceriotti
Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace…
Fast and Accurate Uncertainty Estimation in Chemical Machine Learning
Felix Musil, Michael J. Willatt, Mikhail A. Langovoy +1
We present a scheme to obtain an inexpensive and reliable estimate of the uncertainty associated with the predictions of a machine-learning model of atomic and molecular properties…