cell2mol: encoding chemistry to interpret crystallographic data

S Vela, R Laplaza, Y Cho, C Corminboeuf - Npj Computational …, 2022 - nature.com
The creation and maintenance of crystallographic data repositories is one of the greatest
data-related achievements in chemistry. Platforms such as the Cambridge Structural …

SPAHM(a,b): Encoding the Density Information from Guess Hamiltonian in Quantum Machine Learning Representations

KR Briling, Y Calvino Alonso, A Fabrizio… - Journal of Chemical …, 2024 - ACS Publications
Recently, we introduced a class of molecular representations for kernel-based regression
methods─ the spectrum of approximated Hamiltonian matrices (SPAHM)─ that takes …

The resolution-vs.-accuracy dilemma in machine learning modeling of electronic excitation spectra

P Kayastha, S Chakraborty, R Ramakrishnan - Digital Discovery, 2022 - pubs.rsc.org
In this study, we explore the potential of machine learning for modeling molecular electronic
spectral intensities as a continuous function in a given wavelength range. Since presently …

Preliminary in silico studies of the interactions of certain genotoxic azo dyes with different double-stranded DNA conformations

ES İstifli - Colorants, 2022 - mdpi.com
Organic azo dyes, which are widely used in industrial, health and cosmetic fields, pose
genotoxic risks due to their chemical structures; however, the molecular details of the …

SPAM(a,b): encoding the density information from guess Hamiltonian in quantum machine learning representations

KR Briling, YC Alonso, A Fabrizio… - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, we introduced a class of molecular representations for kernel-based regression
methods--the spectrum of approximated Hamiltonian matrices (SPA $^\mathrm {H} $ M)--that …