Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven si ...
This paper presents a novel activity-based demand model that combines an optimisation framework for continuous temporal scheduling decisions (i.e. activity timings and durations) with traditional discrete choice models for non-temporal choice dimensions (i ...
Clusters in the (Be, B, C)@Si-n((0,1,2+)) (n = 6-10) series, isoelectronic to Si-n(2-), present multiple symmetric structures, including rings, cages and open structures, which the doping atom stabilizes using contrasting bonding mechanisms. The most strik ...
Temperature and suspended particle distribution were surveyed and modeled in two high-Alpine reservoirs in Switzerland, connected by pumped-storage operations for similar to 30 years. Due to different glacier coverage of the catchments, the two reservoirs ...
A method for automatic localization of objects in a mask. The method includes building a dictionary or atoms, wherein each atom models the presence of one object at one location and iteratively determining the atom of said dictionary which is best correlat ...
