Cargando…
SPA(H)M: the spectrum of approximated Hamiltonian matrices representations
Physics-inspired molecular representations are the cornerstone of similarity-based learning applied to solve chemical problems. Despite their conceptual and mathematical diversity, this class of descriptors shares a common underlying philosophy: they all rely on the molecular information that determ...
Autores principales: | Fabrizio, Alberto, Briling, Ksenia R., Corminboeuf, Clemence |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
RSC
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9189859/ https://www.ncbi.nlm.nih.gov/pubmed/35769206 http://dx.doi.org/10.1039/d1dd00050k |
Ejemplares similares
-
Hamiltonian-Reservoir Replica Exchange and Machine
Learning Potentials for Computational Organic Chemistry
por: Fabregat, Raimon, et al.
Publicado: (2020) -
Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts
por: Gallarati, Simone, et al.
Publicado: (2021) -
Data-powered augmented volcano plots for homogeneous catalysis
por: Wodrich, Matthew D., et al.
Publicado: (2020) -
Electron density learning of non-covalent systems
por: Fabrizio, Alberto, et al.
Publicado: (2019) -
Evanescent Wave Approximation for Non-Hermitian Hamiltonians
por: Militello, Benedetto, et al.
Publicado: (2020)